应用人工智能研究
type: channel
description: （AAIR）是一本专注于人工智能领域前沿研究与创新实践的国际期刊，致力于为全球学者、研究人员和行业专家提供一个高端学术交流平台，推动人工智能理论与技术的持续发展，加速其在多领域的深度融合与广泛应用。​ 本期刊聚焦人工智能的核心研究方向，涵盖机器学习、深度学习、自然语言处理、计算机视觉、机器人技术、智能系统、数据挖掘、知识图谱等多个领域，既欢迎基础理论研究的突破性成果，也重视具有重要应用价值的创新性实践探索。通过发表高质量的原创研究论文、综述文章、案例研究及技术报告，全面展示人工智能领域的最新动态与发展趋势。​
publisher: CHINA SCIENCE AND TECHNOLOGY DEVELOPMENT PRESS
language: zh-Hans
publication name: 应用人工智能研究
issn: 3105-0379
items: Map of Geographical Science Based on Artificial Intelligence
items: https://journal.innoviair.cn/index.php/AAIR/zh_Hans/article/view/42
items: Innovative Research on Cracking the Personalized Service Management of Artificial Intelligence Libraries
items: Application of AI Models in Dynamic Talent Adaptation between Industry and Education: A Case Study of Data from Digital Genealogy Cloud Platform
items: Language, Consciousness, and Manifestation: Towards a Pragmatic-Cognitive Framework for Next-Generation Neural Language Systems
items: Against the Backdrop of the Digital Economy: AI Empowers Innovation and Entrepreneurship Education for the Integration of Industry and Education
items: Research on the Impact Mechanism of Farmers' Digital Literacy on Enhancing Service Satisfaction of Power Grid Companies: An Implementation Path Based on the Interpretability of Machine Learning Models
items: Applying Radiomics and Deep Learning to Investigations into Seafarers' Health Status
items: A Learnable Frequency Gated DCT Denoising Network
items: The coupled application of GIS digital Twin and AI reinforcement learning
items: A lightweight AI model with ethics priority: Differential English teaching practice in junior middle schools under the dimension of cultural competence
items: On How Artificial Intelligence Drives Innovation in International Chinese Language Education
items: Artificial Intelligence in Pharmaceutical Formulation: A Comprehensive Review
items: To whom exactly does inspiration belong? The creative rights and aesthetic boundaries behind AI-generated works
items: From "Knowing how to farm" to "Understanding Data" - The Reengineering of Farmers' Skills and Rural Development in the Context of Smart Agriculture
items: Intelligent Auxiliary System for Chronic Disease Prevention and Treatment Based on Information Technology and Its application in Improving Patients' Trust Predicament
items: After machines began to "learn to think" - the boundaries of automation and the repositioning of the labor force in the transformation of manufacturing
items: Innovative Application of Artificial Intelligence Algorithms in Credit Scoring: Taking specific products in the field of consumer finance as the research object
items: From "Passive Congestion" to "Active Scheduling" — Rebuilding Travel Experience and Resource Allocation for Intelligent Transportation Networks

Map of Geographical Science Based on Artificial Intelligence
type: item
description: As a core tool for integrating the geographical knowledge system and revealing conceptual associations, the traditional construction mode of the basic concept map of geographical science is confronted with bottlenecks such as single data dimension, shallow association mining, and lagging dynamic update. The rise of artificial intelligence technology offers a new path to break through the above limitations. Through the deep integration of algorithms such as machine learning, deep learning, and natural language processing with geographical science theories, intelligent upgrades in concept extraction, relationship modeling, and map optimization can be achieved. This paper systematically reviews the key technologies for constructing the basic concept map of geographic science based on artificial intelligence, including multi-source geographic data preprocessing methods, intelligent concept recognition and classification models, and dynamic relationship mining algorithms, and deeply analyzes the technical characteristics and applicable scenarios of different construction methods. The application value is expounded from three dimensions: the sorting out of the geographical knowledge system, the intelligent solution of geographical problems, and the empowerment of interdisciplinary integration. Finally, the future research directions are prospected to provide references for the intelligent development and practical application of geographical science knowledge graphs.
subject: 文章
  topic: section
subject: Artificial Intelligence
  topic: keywords
subject: Geographical science
  topic: keywords
subject: Concept map Construction method
  topic: keywords
subject: Application value
  topic: keywords
creator: Lizaoa Li
rights: ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0
date: 2025-12-23
publication date: 2025-12-23
doi: 10.65455/dhsph777

https://journal.innoviair.cn/index.php/AAIR/zh_Hans/article/view/42
type: item
title: AI-Driven Intellectual Property: Building and Empirical Testing of an Innovative Startup Collaborative Management Model-Analysis of Cross-Legal Domain Data in the Guangdong-Hong Kong-Macao Greater Bay Area
description: Abstract: With the rapid advancement of artificial intelligence technology, the collaborative management of intellectual property and innovation-driven entrepreneurship faces new opportunities and challenges. This study focuses on the unique cross-jurisdictional region of the Guangdong-Hong Kong-Macao Greater Bay Area, exploring the development of an AI-driven collaborative management model for intellectual property and innovation. Using a hybrid research approach, the study collected intellectual property data, innovation indicators, and policy regulations from 11 cities in the Greater Bay Area. Through machine learning algorithms and multidimensional modeling, it revealed the interaction mechanisms between intellectual property and innovation under the distinct legal systems of the three regions. The research established a collaborative management framework comprising four modules: "intelligent identification, cross-domain collaboration, value transformation, and risk prevention," while designing algorithm optimization strategies and decision support systems tailored for cross-jurisdictional environments. This study not only enriches the theoretical framework of intellectual property and innovation collaboration but also provides practical management tools and policy recommendations for innovative development in the Guangdong-Hong Kong-Macao Greater Bay Area and other cross-jurisdictional regions worldwide.
subject: 文章
  topic: section
subject: AI-driven
  topic: keywords
subject: intellectual property
  topic: keywords
subject: innovation and entrepreneurship
  topic: keywords
subject: collaborative management model
  topic: keywords
subject: Guangdong-Hong Kong-Macao Greater Bay Area
  topic: keywords
creator: Guo Xiaodi
creator: Jingjiang Deng
creator: Junming Liang
creator: Chen Chen
rights: ##submission.copyrightStatement##
date: 2025-12-04
publication date: 2025-12-04
doi: 10.65455/85c92315

Innovative Research on Cracking the Personalized Service Management of Artificial Intelligence Libraries
type: item
description: Against the backdrop of the accelerated advancement of Artificial intelligence transformation, emerging technologies have become the core driving force for the upgrading of library services. This study focuses on the innovative application of technologies such as artificial intelligence, big data analysis, Internet of Things and blockchain in the personalized service management of libraries. Through methods such as literature analysis, case studies and questionnaire surveys (327 valid samples), a three-dimensional model of "technology empowerment - service reconfiguration - management collaboration" is constructed. Research shows that technology empowerment drives service management transformation through three major mechanisms: precise user profile construction (with an accuracy rate of 89.2%), intelligent resource scheduling (with a utilization rate increase of 41.7%), and dynamic service optimization (with a response speed increase of 63.5%). Empirical cases show that user satisfaction has increased by 35.8% after technology empowerment, but the issues of data security (68.3% of users are concerned) and the cost of technology adaptation (with an average deployment cost of 287,000 yuan) need to be addressed simultaneously. Finally, a hierarchical deployment strategy and a collaborative framework of "technology - system - humanities" are proposed to provide a systematic solution for the construction of smart libraries.
subject: 文章
  topic: section
subject: Emerging technology
  topic: keywords
subject: Library
  topic: keywords
subject: Personalized service
  topic: keywords
subject: Service management
  topic: keywords
subject: Wisdom empowerment
  topic: keywords
subject: Privacy computing
  topic: keywords
creator: Nan Liu
rights: ##submission.copyrightStatement##
date: 2025-12-12
publication date: 2025-12-12
doi: 10.65455/4mv0z378

Application of AI Models in Dynamic Talent Adaptation between Industry and Education: A Case Study of Data from Digital Genealogy Cloud Platform
type: item
description: This study examines the application of AI models in dynamic talent adaptation between industry and education, using data from the Digital Genealogy Cloud Platform as a research sample. It analyzes current challenges in industry-education talent alignment and elaborates on the pivotal role of AI models. Through in-depth mining and analysis of platform data, the research demonstrates how AI models leverage big data, artificial intelligence, and knowledge graphs to achieve precise digital integration across industrial chains, talent pipelines, and educational systems. The findings reveal that AI models not only assist vocational colleges in optimizing program structures and innovating talent cultivation models, but also facilitate deep collaboration between schools and enterprises. This enhances the alignment between talent development and industrial demands, providing robust support for the digital transformation and high-quality development of vocational education. Additionally, it offers new perspectives and practical solutions to address fundamental issues in industry-education integration.
subject: 文章
  topic: section
subject: AI model
  topic: keywords
subject: industry-education talent
  topic: keywords
subject: dynamic adaptation
  topic: keywords
subject: digital genealogy cloud platform
  topic: keywords
subject: vocational education
  topic: keywords
creator: Jingjiang Deng
creator: Junming Liang
creator: Chen Chen
creator: Weijian Huang
rights: ##submission.copyrightStatement##
date: 2025-12-04
publication date: 2025-12-04
doi: 10.65455/srezr230

Language, Consciousness, and Manifestation: Towards a Pragmatic-Cognitive Framework for Next-Generation Neural Language Systems
type: item
description: This paper proposes a geometric model of language and consciousness designed to speak simultaneously to linguistic theory and neural language systems. Conscious experience is modelled as a multidimensional sphere of concurrently available potentials—perceptions, emotions, intentions, and pre-verbal structures—while language is treated as a tangent drawn along the sphere’s surface. On this view, an utterance never exhausts a speaker’s inner state; it selects a thin, ordered path across a much richer configuration, necessarily highlighting some regions while leaving others implicit. Building on this model, the paper reframes speech acts, dialogue, public speaking, divination, and artistic creation as different ways of stabilising and steering what appears on the surface of the sphere. Manifestation is defined as the family of processes by which internal potentials become publicly available forms, of which linear language is only one special, highly constrained channel. Neural language systems are then reconsidered in this light: current architectures are powerful generators of tangents but possess no explicit representation of the spherical states, intentions, or collective fields from which human utterances emerge. The paper does not propose a specific architecture but outlines a pragmatic-cognitive framework in which future systems would model (i) intention as the choice of tangent direction, (ii) context as the evolving shape of individual and shared spheres, and (iii) attention as a mechanism for controlling which regions are allowed to manifest. By articulating language, consciousness, and manifestation within a single geometric metaphor, the paper aims to provide conceptual tools for rethinking both human communication and the design of next-generation neural language systems.
subject: 文章
  topic: section
subject: Language
  topic: keywords
subject: Consciousness
  topic: keywords
subject: Manifestation
  topic: keywords
subject: Pragmatics
  topic: keywords
subject: Cognition
  topic: keywords
subject: Natural Language Processing
  topic: keywords
subject: Neural Language Systems
  topic: keywords
creator: Anni Li
rights: ##submission.copyrightStatement##
date: 2025-12-13
publication date: 2025-12-13
doi: 10.65455/cnbj7s21

Against the Backdrop of the Digital Economy: AI Empowers Innovation and Entrepreneurship Education for the Integration of Industry and Education
type: item
description: The digital economy and AI technologies are driving transformations in industry-education integration models, yet traditional practices face challenges such as mismatched supply and demand and inefficient resource allocation. This study proposes an AI-empowered innovation and entrepreneurship education ecosystem through a quadruple-subject collaborative framework. Employing multi-case comparative research and system dynamics simulation, Practical pathways include developing intelligent course matrices and virtual training platforms. Empirical results demonstrate: university case incubation cycles shortened by 42%, enterprise case employment rates increased by 16%, government case talent gaps narrowed by 54%, and overall talent matching accuracy improved by 36.5%. AI technology effectively resolves industry-education integration challenges, offering a new paradigm for digital economy talent cultivationy
subject: 文章
  topic: section
subject: digital economy
  topic: keywords
subject: artificial intelligence
  topic: keywords
subject: integration of production and education
  topic: keywords
subject: double innovation education
  topic: keywords
creator: Qiang Liu
rights: ##submission.copyrightStatement##
date: 2025-12-13
publication date: 2025-12-13
doi: 10.65455/nh2jc129

Research on the Impact Mechanism of Farmers' Digital Literacy on Enhancing Service Satisfaction of Power Grid Companies: An Implementation Path Based on the Interpretability of Machine Learning Models
type: item
description: This study focuses on the "service supply - user demand" tension issue in the service satisfaction of power grid companies during the process of Chinese-style modernization. China has achieved remarkable results in the construction of power grid infrastructure, but there are regional differences in user satisfaction, especially in rural areas. Under the background of digitalization of power grids, although digital technology brings benefits, the differences in digital infrastructure and usage levels in rural areas have led to a digital divide, shifting from an "access gap" to a "capability gap". Digital literacy has become the key to enhancing service satisfaction. In view of the existing research deficiencies, this paper constructs an index system for measuring and evaluating the digital literacy of farmers, and uses the XGBoost and SHAP models to quantitatively analyze the influence mechanism and implementation path of digital literacy on the service satisfaction of power grid companies. The research results can provide a scientific basis for power grid companies to precisely optimize services, helping them identify key influencing factors, optimize the allocation of service resources, enhance service satisfaction, and promote the high-quality development of power grid services.
subject: 文章
  topic: section
subject: Farmers' Digital Literacy
  topic: keywords
subject: Power Grid Companies
  topic: keywords
subject: Service Satisfaction
  topic: keywords
subject: XGBoost
  topic: keywords
subject: SHAP Explainability
  topic: keywords
creator: Yuxuan Tong
creator: Zewei Zhang
rights: ##submission.copyrightStatement##
date: 2025-12-03
publication date: 2025-12-03
doi: 10.65455/6dwx3a82

Applying Radiomics and Deep Learning to Investigations into Seafarers' Health Status
type: item
description: Objective This study aimed to conduct a retrospective investigation into the prevalence of fatty liver disease and gallstones among seafarers, explore the relevant influencing factors, and further evaluate the application value of deep learning-based radiomics in intelligent screening, quantitative diagnosis, and risk prediction of these hepatobiliary diseases. Methods A total of 7232 male seafarers who underwent abdominal ultrasound (Apollo 500/Esaote MyLab Gamma system), blood lipid testing (Hitachi 7180 automatic biochemical analyzer), and body mass index (BMI) measurement at the Physical Examination Center of Shanghai Waterway Hospital from June 2022 to November 2023 were randomly selected as research subjects. Traditional statistical methods (chi-squared test, correlation analysis, t-test) were used to analyze the correlation between clinical indicators (BMI, blood lipids) and disease incidence. Meanwhile, a deep learning framework integrating U-Net-based image segmentation and MobileNetV2-based classification was constructed: 1) Automatically segmenting the liver and gallbladder regions of interest (ROIs) from ultrasound images to avoid subjective errors of manual segmentation; 2) Extracting high-dimensional radiomic features (texture, gray level, morphological features) through the pre-trained deep learning model, replacing traditional manual feature selection; 3) Establishing a dual disease prediction model (fatty liver/gallstones) by fusing clinical indicators (BMI, blood lipids) and deep radiomic features. Results With the increase in BMI, the incidence rates of hyperlipidemia and fatty liver disease showed a linear positive correlation (r=0.98, t=6.83, df=2, P<0.05). The deep learning model achieved excellent performance in disease diagnosis: for fatty liver disease, the area under the receiver operating characteristic curve (AUC) was 0.93, accuracy 90.2%, recall 88.5%, and specificity 89.8%, which was significantly higher than traditional manual ultrasou…
subject: 文章
  topic: section
subject: fatty liver disease
  topic: keywords
subject: gallstones
  topic: keywords
subject: radiomics
  topic: keywords
subject: deep learning
  topic: keywords
creator: Huiming KANG
creator: Xiaoqing LI
creator: Mingyue FENG
creator: Wei WANG
creator: Shidi LIU
creator: Shaocong LIANG
creator: Cuiliu ZHOU
creator: De KANG
creator: Lingling CHEN
rights: ##submission.copyrightStatement##
date: 2025-12-09
publication date: 2025-12-09
doi: 10.65455/nqcbkw66

A Learnable Frequency Gated DCT Denoising Network
type: item
description: Most DCT based denoising still follows fixed rules, like hard or soft thresholds, keep only low frequency parts, or simple sub band Wiener filters. On real photos these rules usually trade detail for smoothness, or the other way around. We build a learnable frequency gated denoising network. On top of differentiable orthogonal DCT and IDCT, the model learns masks and gains for high and low frequency channels, and it adds a light low resolution global attention module to catch long range context. With an image level residual skip, the reconstructions look clean and sharp. In our small setup the method lifts PSNR and SSIM a lot compared to a pure DCT baseline, from 11.89 dB and 0.2915 to 25.05 dB and 0.945. In short, we turn a rule driven DCT pipeline into a learnable one, so we keep the frequency prior and still get the robustness of modern learning.
subject: 文章
  topic: section
subject: image denoising
  topic: keywords
subject: discrete cosine transform
  topic: keywords
subject: frequency domain modeling
  topic: keywords
subject: multi scale attention
  topic: keywords
subject: global residual
  topic: keywords
subject: image restoration
  topic: keywords
creator: Haonian Cao
rights: ##submission.copyrightStatement##
date: 2025-12-09
publication date: 2025-12-09
doi: 10.65455/p24ghq94

The coupled application of GIS digital Twin and AI reinforcement learning
type: item
description: In response to the intelligent governance demands of complex scenarios such as smart cities and smart water conservancy, this paper explores the coupled application of GIS digital twins and AI reinforcement learning. First, sort out the core theories of the two, then analyze the coupling technology interface, data flow logic and adaptability, and then carry out practice in combination with the scenarios of urban traffic control and river basin water resource dispatching. Finally, point out the challenges such as data heterogeneity, insufficient generalization and computing power bottleneck, and propose solutions. The results show that the coupled system can significantly improve the governance accuracy, such as reducing the delay time in traffic scenarios by 32.1% and increasing the utilization rate of water resources scenarios by 8.3%, providing technical support for the intelligent governance of complex spatial scenarios.
subject: 文章
  topic: section
subject: GIS
  topic: keywords
subject: Digital Twin
  topic: keywords
subject: AI
  topic: keywords
subject: reinforcement learning
  topic: keywords
subject: Coupled application
  topic: keywords
subject: Intelligent governance
  topic: keywords
subject: Urban traffic control
  topic: keywords
subject: Water resources dispatching in river basins
  topic: keywords
creator: ZiYi Xia
rights: ##submission.copyrightStatement##
date: 2025-12-02
publication date: 2025-12-02
doi: 10.65455/d792e032

A lightweight AI model with ethics priority: Differential English teaching practice in junior middle schools under the dimension of cultural competence
type: item
description: Abstract: In view of the long-standing dilemma of "pseudo-stratification" in junior middle school English stratification teaching and the ethical controversy caused by artificial intelligence technology, this study constructs a lightweight teaching framework with ethics priority. By integrating federated learning and non-inductive data acquisition technology, a collaborative model of "three-layer dynamic grouping and four-dimensional strategy matrix" was innovatively designed, and a 6-month controlled experiment was carried out among 326 students covering eastern cities, central counties and towns, and western villages. The empirical results show that the hierarchical accuracy rate is improved to 89%, the grammatical error rate is significantly reduced by 31%, and the cultural understanding is increased by 44%. At the same time, the hierarchical informed agreement reduces the parent data withdrawal request rate to 0.9%. The framework uses mobile phone sensors to achieve low-cost deployment. Through dynamic diagnosis and ethical compliance design, it provides a scalable differentiated teaching path for resource-weak areas, and promotes the transformation of educational equity from concept to empirical evidence.
subject: 文章
  topic: section
subject: Differential teaching
  topic: keywords
subject: Federated Learning
  topic: keywords
subject: Educational equity
  topic: keywords
creator: Hui Nie
rights: ##submission.copyrightStatement##
date: 2025-12-13
publication date: 2025-12-13
doi: 10.65455/es208a12

On How Artificial Intelligence Drives Innovation in International Chinese Language Education
type: item
description: The rapid development of artificial intelligence (AI) technology is permeating all sectors of society with unprecedented depth and breadth. In the field of international Chinese language education, AI has evolved far beyond being a mere auxiliary tool like the "slide projector" or "tape recorder" of the past; instead, it has become a core driving force leading this field toward a profound paradigmatic revolution. This paper systematically elaborates on how AI technology promotes systematic innovation and upgrading in international Chinese language education from five core dimensions: the personalized reconstruction of teaching models, the intelligent generation of teaching resources, the full-process reform of teaching evaluation, the strategic transformation of teachers' roles, and the global integration of educational ecosystems. Meanwhile, the paper also takes a prudent look at challenges that may arise during the process of technology integration, such as algorithmic bias, lack of emotional interaction, the digital divide, and the alienation of the essence of education. Finally, it points out that the future development path must involve the in-depth integration of "artificial intelligence" and "humanistic guidance," aiming to build a new, human-machine collaborative, ecologically sound, and sustainable international Chinese language education system. This system will provide new possibilities and fundamental pathways for achieving more equitable, high-quality, and inclusive global Chinese language education.
subject: 文章
  topic: section
subject: Artificial Intelligence
  topic: keywords
subject: International Chinese Language Education
  topic: keywords
subject: Educational Innovation
  topic: keywords
subject: Personalized Learning
  topic: keywords
subject: AIGC
  topic: keywords
subject: Paradigmatic Revolution
  topic: keywords
creator: Fanqi Meng
rights: ##submission.copyrightStatement##
date: 2025-12-12
publication date: 2025-12-12
doi: 10.65455/023h4s18

Artificial Intelligence in Pharmaceutical Formulation: A Comprehensive Review
type: item
description: Objective: This review systematically evaluates the current status, application scenarios, and implementation effectiveness of artificial intelligence (AI) technologies in pharmaceutical formulation. It analyzes existing challenges and future directions to provide a technical reference for rational formulation development. Methods: We retrieved literature published between 2020 and 2025 from core databases including PubMed, MEDLINE, Embase, and Cochrane Library, focusing on high-quality studies applying AI to formulation design, optimization, production, and quality control. A systematic review methodology was employed to summarize technical approaches, performance metrics, and comparative outcomes between AI and traditional methods across various formulation types. Results: Analysis of 67 qualified studies revealed significant advantages of AI technologies across multiple formulation development stages. In drug delivery system design, AI-assisted nanocarrier development reduced development time by 60%-70% on average. For formulation optimization, AI models achieved 85%-93% accuracy in predicting critical quality attributes, representing a 25%-40% improvement over traditional empirical methods. In manufacturing processes, AI control strategies improved product batch consistency by 30%-50%. Furthermore, AI-driven adaptive learning frameworks demonstrated capability for continuous formulation and process optimization through real-time data integration. Conclusion: Artificial intelligence is fundamentally transforming pharmaceutical formulation development paradigms through data-driven approaches that significantly enhance efficiency, reduce costs, and improve product quality. Despite challenges in data quality, model interpretability, and industrial implementation, ongoing algorithm innovations and multidisciplinary integration are expected to advance pharmaceutical formulation into a new era of precision, personalization, and intelligence.
subject: 文章
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: pharmaceutical formulation
  topic: keywords
subject: machine learning
  topic: keywords
subject: intelligent delivery systems
  topic: keywords
subject: formulation design
  topic: keywords
subject: process control
  topic: keywords
subject: Quality by Design
  topic: keywords
subject: formulation informatics
  topic: keywords
creator: Peng WU
creator: Peiyu ZANG
rights: ##submission.copyrightStatement##
date: 2025-12-02
publication date: 2025-12-02
doi: 10.65455/nshrsr55

To whom exactly does inspiration belong? The creative rights and aesthetic boundaries behind AI-generated works
type: item
description: With the rapid development of AI technology, its application in art creation is becoming more and more popular. An automatic generation system of AI art works can generate works of unique style and aesthetic value by means of deep learning algorithms. However, the question of creative ownership behind AI-generated works has always been ambiguous. In this paper, we discuss creative rights and aesthetic boundaries behind AI-generated works. However, there has not been a clear legal definition. In spite of this, AI's automatic generation of artworks has become a major trend. At present there are no laws or regulations that stop the development of AI + art.. On the basis of the above results, we have developed an AI generation system. Using AI technology, it automatically generates artwork that creators want.In addition, the public often believes that the ownership of AI-generated artworks belongs to the AI platform. In fact, the AI system is merely an auxiliary tool, and the creative inspiration still comes from the author. Therefore, this system can generate a contract for the AI system platform to this AI system waive the copyright.Register your copyright on the website of the National Copyright Center to avoid legal disputes and protect the legitimate rights and interests of creators.
subject: 文章
  topic: section
subject: AI + Art Automatic art creation
  topic: keywords
subject: Creation Right
  topic: keywords
subject: Aesthetic Edge Deep Learning
  topic: keywords
creator: Zhongyu Xu
rights: ##submission.copyrightStatement##
date: 2025-09-15
publication date: 2025-09-15
doi: 10.65455/aair5915

From "Knowing how to farm" to "Understanding Data" - The Reengineering of Farmers' Skills and Rural Development in the Context of Smart Agriculture
type: item
description: With information technology widely applied to agriculture sector, intelligent agriculture has become a new trend of modern agriculture. In this paper, we explore the framework, design and application of smart agricultural data analysis system. With the integration of Internet of Things, Big Data and Artificial Intelligence, this system provides precise decision support to farmers in agricultural production, optimizing agricultural production process, increasing agricultural production efficiency and product quality. In this paper, the overall design, every level design, database design, security design, main functions are elaborated in detail. The validity of this system has been verified by an actual application case. With the development of technology and development of agriculture information system, it is expected that smart agricultural data analysis system will play an important role in broader agriculture scenarios..
subject: 文章
  topic: section
subject: AI + Agriculture Data
  topic: keywords
subject: Analysis Internet of Things
  topic: keywords
subject: Artificial Intelligence Agriculture Information
  topic: keywords
creator: can wan
rights: ##submission.copyrightStatement##
date: 2025-09-15
publication date: 2025-09-15
doi: 10.65455/aair5911

Intelligent Auxiliary System for Chronic Disease Prevention and Treatment Based on Information Technology and Its application in Improving Patients' Trust Predicament
type: item
description: Along with the rapid development of information technology, there are unprecedented opportunities and challenges in the area of chronic diseases. Chronic diseases' long-term nature, complexity and impact on patients' quality of life make it clear that traditional prevention model can not meet patients' diverse needs and increase their trust. It aims at providing personalized and accurate prevention and treatment plans based on AI, Big Data, Internet of Things, and other advanced technologies in order to improve doctor-patient trust. In this paper, we deeply discuss the system's overall structure, design, main functions, and its application effect on patients' trust dilemma.
subject: 文章
  topic: section
subject: AI+Healthcare
  topic: keywords
subject: Information Technology;Prevention & Treatment for Chronic Diseases
  topic: keywords
subject: Intelligent Auxiliary System
  topic: keywords
subject: Doctor-Patient Relationship
  topic: keywords
creator: Jiaqi Liu
rights: ##submission.copyrightStatement##
date: 2025-09-15
publication date: 2025-09-15
doi: 10.65455/aair5615

After machines began to "learn to think" - the boundaries of automation and the repositioning of the labor force in the transformation of manufacturing
type: item
description: Along with industry 4.0 advancement, Intelligent Manufacturing becomes an important trend of manufacturing industry. As a key component in intelligent manufacturing, intelligent control system can not only improve production efficiency, product quality, but also define labor's function and value. In this paper, a deeper discussion is made on the design framework, multi-level framework and application effect of intelligent control system for machinery and equipment in manufacturing enterprises. Through building integrated intelligent control system, a new automated production model is put forward, which aims at intelligent management of production equipment, automatic optimization of production process, and efficient redeployment of labor force. With advanced sensor technology, AI algorithm and big data analysis, this system is able to significantly enhance production efficiency, reduce cost and provide powerful support to manufacturing industry in the future. As technology advances and manufacturing requirements continue to change, Smart Control System is expected to play an important role under broader industrial scenarios, driving manufacturing towards intelligent, efficient and sustainable development.
subject: 文章
  topic: section
subject: AI + Manufacturing Machinery & Equipment
  topic: keywords
subject: Intelligent Control Automation Labor Reorienting
  topic: keywords
creator: Lijun Wang
rights: ##submission.copyrightStatement##
date: 2025-06-15
publication date: 2025-06-15
doi: 10.65455/aair5614

Innovative Application of Artificial Intelligence Algorithms in Credit Scoring: Taking specific products in the field of consumer finance as the research object
type: item
description: This paper focuses on specific products in consumer finance and explores the innovative application of artificial intelligence algorithms in credit scoring. By analyzing the technical foundation and current situation, this paper expounds the core technological innovations such as deep learning, tree model integration, and graph neural networks, and solves the problems of data fusion, model optimization, and interpretability. Empirical research shows that artificial intelligence algorithms outperform traditional models in multiple indicators.
subject: 文章
  topic: section
subject: Artificial Intelligence algorithm Credit score
  topic: keywords
subject: Consumer finance Deep learning Model interpretability
  topic: keywords
creator: Feng Yuan
rights: ##submission.copyrightStatement##
date: 2025-06-15
publication date: 2025-06-15
doi: 10.65455/aair5612

From "Passive Congestion" to "Active Scheduling" — Rebuilding Travel Experience and Resource Allocation for Intelligent Transportation Networks
type: item
description: Along with the acceleration of urbanization, traffic congestion becomes an important factor restricting urban development and improving residents' quality of life. In order to cope with complex traffic requirements, traditional traffic management models seem to be inadequate, often falling into passive congestion. The emergence of intelligent transport networks brings new hope to the solution to this problem. In this paper, the theory basis, technology structure, key technology and application practice are deeply discussed. The aim of this paper is to achieve a transition from passive congestion to active dispatching. In this paper, by constructing a framework of intelligent traffic system, analyzing each level design, analyzing main functional applications, it reveals that intelligent traffic network plays an important role in alleviating traffic congestion, improving traffic safety and promoting sustainable traffic development. Finally, it looks forward to its future development..
subject: 文章
  topic: section
subject: Intelligent traffic reconstruction
  topic: keywords
subject: Travel experience
  topic: keywords
subject: Resource allocation
  topic: keywords
subject: Traffic congestion Active scheduling
  topic: keywords
creator: Baochao Liang
rights: ##submission.copyrightStatement##
date: 2025-06-15
publication date: 2025-06-15
doi: 10.65455/aair5611