[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4819":3,"related-4819":58},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":17,"tags":19,"primary_topic":8,"secondary_topics":23,"classification":24,"search_phrases":39,"slug":42,"view_count":43,"doi":44,"paper":45,"created_at":57},4819,"Governance and operational management of public photovoltaic systems: A decision support framework for decentralized installations","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-10705468\u002Fv1","Governance and operational management of public photovoltaic systems: A decision support framework for decentralized installations。Research Square",null,"Research Square","2026-10-12T00:00:00Z","论文",10,false,0,{"impact":14,"substance":14,"depth":14,"authority":14,"freshness":14,"relevant":14,"comment":16},"主题为公共光伏系统的治理与运营管理，与三农、农业信息化、智慧农业等无关，不予入选。",[18],{"name":9,"url":6},[20,21,22],"决策支持","公共光伏","分布式能源",[],{"status":25,"locked":13,"version":26,"method":27,"evidence":28},"needs_review","2026-10-22.2","rules",{"candidates":29,"agricultural_evidence":13,"reason":38},[30],{"code":31,"score":32,"supported":33,"title":34,"abstract":36,"tags":37},"I2",12,true,[35],"decision support",[35],[20],"农业相关性需要复核",[40,41],"公共光伏系统 分布式安装 决策支持","分布式能源 公共光伏 决策支持","公共光伏系统分布式安装决策支持-4819",2,"10.21203\u002Frs.3.rs-10705468\u002Fv1",{"doi":44,"openalex_id":46,"authors":47,"venue":9,"cited_by_count":14,"oa_url":54,"card":8,"direction":55,"ingested_from":56},"W7221571739",[48,51],{"name":49,"orcid":50},"Manoel Henrique Alves","https:\u002F\u002Forcid.org\u002F0000-0002-1392-9607",{"name":52,"orcid":53},"Fabiano Perin Gasparin","https:\u002F\u002Forcid.org\u002F0000-0001-9422-6948","https:\u002F\u002Fwww.researchsquare.com\u002Farticle\u002Frs-10705468\u002Flatest.pdf","智慧农业 \u002F 农业物联网","openalex","2026-10-13T23:30:16.091921Z",{"total":59,"page":60,"page_size":59,"items":61},6,1,[62,143,195,267,341,413],{"id":63,"title":64,"url":65,"summary":66,"summary_zh":67,"content":8,"source_name":68,"source_url":65,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":69,"score_detail":70,"sources":75,"tags":77,"primary_topic":82,"secondary_topics":88,"classification":89,"search_phrases":124,"slug":127,"view_count":60,"doi":128,"paper":129,"created_at":142},4799,"Applications of Neutrosophic Topology in the Indian Context: A Review and Emerging Research Directions","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23318355","AbstractNeutrosophic topology is an extension of classical topology designed to represent informationcharacterized by truth, indeterminacy, and falsity simultaneously. Unlike classical mathematicalmodels, which generally assume that an element either belongs or does not belong to a set,neutrosophic approaches permit the coexistence of partial truth, uncertainty, and contradiction. Thisfeature makes neutrosophic topology potentially useful for modelling complex systems in whichinformation is incomplete, inconsistent, imprecise, or dynamically changing. India, with its largeand heterogeneous population, geographically diverse environment, rapidly expanding digitalinfrastructure, and complex decision-making systems, provides several important contexts in whichsuch mathematical frameworks may be investigated. This article reviews the development ofneutrosophic topology and examines its potential and emerging applications in the Indian context.Particular attention is given to geographical information systems, medical diagnosis, data mining,decision-making, smart-city management, environmental monitoring, agricultural informationsystems, transportation networks, and information systems. Existing Indian contributionsdemonstrate that neutrosophic topological structures are increasingly being studied in connectionwith data analysis and decision problems. The article also identifies limitations in current research,particularly the gap between theoretical topological constructions and validated real-world datasets.Finally, several future research directions are proposed, including integration with geographicinformation systems, artificial intelligence, Internet-of-Things data, remote sensing, healthcareanalytics, and multi-criteria decision-making. The study concludes that neutrosophic topology offersa promising mathematical framework for representing uncertainty and inconsistency in Indian socio-technical and environmental systems, provided that future research emphasizes empirical validation and computational implementation. Keywords: Neutrosophic topology; neutrosophic sets; uncertainty; indeterminacy; fuzzy topology; GIS; decision making; data mining; India; mathematical modelling.","摘要：中智拓扑学（Neutrosophic topology）是经典拓扑学的扩展，旨在同时表示由真、不确定和假所刻画的信息。与通常假设元素要么属于某集合、要么不属于某集合的经典数学模型不同，中智方法允许部分真、不确定性和矛盾同时存在。这一特性使中智拓扑学在建模信息不完整、不一致、不精确或动态变化的复杂系统方面具有潜在价值。印度拥有庞大且异质的人口、地理多样的环境、快速扩展的数字基础设施以及复杂的决策系统，为研究此类数学框架提供了若干重要场景。本文综述了中智拓扑学的发展，并考察其在印度语境下的潜力和新兴应用。特别关注地理信息系统、医学诊断、数据挖掘、决策、智慧城市管理、环境监测、农业信息系统、交通网络和信息系统等领域。印度已有的研究成果表明，中智拓扑结构正日益被用于数据分析和决策问题的研究。本文还指出了当前研究的局限性，尤其是理论拓扑构造与经过验证的现实世界数据集之间的差距。最后，提出了若干未来研究方向，包括与地理信息系统、人工智能、物联网数据、遥感、医疗分析和多准则决策的整合。研究认为，中智拓扑学为表示印度社会技术系统和环境系统中的不确定性与不一致性提供了一个有前景的数学框架，前提是未来研究应重视实证验证和计算实现。关键词：中智拓扑学；中智集；不确定性；不确定；模糊拓扑学；地理信息系统；决策；数据挖掘；印度；数学建模。","Zenodo (CERN European Organization for Nuclear Research)",57,{"impact":71,"substance":72,"depth":73,"authority":32,"freshness":71,"relevant":60,"comment":74},8,14,15,"综述性论文，将中智拓扑引入印度农业信息系统、遥感与决策场景，理论价值明确但缺乏实证数据，属细分领域参考。",[76],{"name":68,"url":65},[78,79,80,81,20],"智慧农业","农业人工智能","农业信息化","遥感",{"code":83,"slug":84,"name":85,"path":86,"parent_code":87},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":90,"locked":13,"version":26,"method":27,"evidence":91},"classified",{"candidates":92,"agricultural_evidence":33},[93,99,106,112,119],{"code":83,"score":94,"supported":33,"title":95,"abstract":96,"tags":98},7,[],[81,97],"remote sensing",[81],{"code":100,"score":59,"supported":33,"title":101,"abstract":102,"tags":105},"I4",[],[103,104],"地理信息","GIS",[],{"code":31,"score":107,"supported":33,"title":108,"abstract":109,"tags":111},5,[],[110],"artificial intelligence",[79,20],{"code":113,"score":114,"supported":33,"title":115,"abstract":116,"tags":118},"I5",3,[],[117],"物联网",[],{"code":120,"score":43,"supported":13,"title":121,"abstract":122,"tags":123},"I1",[],[],[80,78],[125,126],"中智拓扑 农业信息系统","农业人工智能 农业信息化 决策支持 智慧农业","中智拓扑农业信息系统-4799","10.5281\u002Fzenodo.23318355",{"doi":128,"openalex_id":130,"authors":131,"venue":68,"cited_by_count":14,"oa_url":65,"card":136,"direction":55,"ingested_from":56},"W7221514584",[132,134],{"name":133,"orcid":8},"N. Raksha Ben",{"name":135,"orcid":8},"G. Helen Rajapushpam",{"tldr":137,"method":138,"finding":139,"direction":140,"opportunity":141},"综述中智拓扑在印度多领域的应用潜力，并指出理论与实证数据脱节的局限。","文献综述，梳理中智拓扑在GIS、决策、农业信息系统等场景的应用。","中智拓扑能刻画不确定性，但缺乏真实数据验证与计算实现。","农业人工智能与决策模型","可将中智拓扑与农业物联网、遥感数据结合，构建可验证的不确定性决策模型。","2026-10-13T23:30:08.455353Z",{"id":144,"title":145,"url":146,"summary":147,"summary_zh":148,"content":8,"source_name":149,"source_url":146,"published_at":150,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":151,"score_detail":152,"sources":156,"tags":158,"primary_topic":8,"secondary_topics":160,"classification":161,"search_phrases":174,"slug":177,"view_count":60,"doi":178,"paper":179,"created_at":194},4664,"Realising the potential of ecological digital twins as decision support tools","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecolmodel.2026.111867","Ecological digital twins are continually updating models used for decision-making. Current progress in ecological digital twinning has focused on overcoming the technological and modelling challenges to create a continually updating system. We argue that attention should now also focus on effectively integrating digital twins into decision-making systems to inform timely action. This requires the direct inclusion of end users and greater focus on the socio-political context. We outline challenges faced in developing such ‘translational’ digital twins from our own experience and translate recommendations for best practice from the transdisciplinary research literature. We champion co-creation as a powerful approach for future translational digital twin projects, especially in larger and more complex research teams.","生态数字孪生（ecological digital twins）是持续更新的模型，用于决策支持。当前生态数字孪生领域的进展主要集中于克服技术与建模方面的挑战，以构建一个持续更新的系统。我们认为，如今还应关注如何将数字孪生有效整合到决策系统中，以支持及时行动。这要求直接纳入终端用户，并更加重视社会政治背景。我们根据自身经验概述了开发此类“转化型”数字孪生所面临的挑战，并从跨学科研究文献中提炼出最佳实践建议。我们倡导将共同创造（co-creation）作为未来转化型数字孪生项目的有力方法，尤其是在规模更大、更为复杂的研究团队中。","Ecological Modelling","2026-10-09T00:00:00Z",72,{"impact":32,"substance":153,"depth":154,"authority":72,"freshness":71,"relevant":60,"comment":155},20,18,"核心期刊论文，提出生态数字孪生从技术构建转向决策支持与共同创造，方法视角新颖，对智慧农业决策系统建设有参考价值。",[157],{"name":149,"url":146},[78,79,20,159],"生态数字孪生",[],{"status":25,"locked":13,"version":26,"method":27,"evidence":162},{"candidates":163,"agricultural_evidence":13,"reason":38},[164,168],{"code":31,"score":12,"supported":33,"title":165,"abstract":166,"tags":167},[35],[],[79,20],{"code":120,"score":94,"supported":33,"title":169,"abstract":170,"tags":173},[],[171,172],"数字孪生","digital twin",[78],[175,176],"生态数字孪生 决策支持","Ecological Modelling 数字孪生","生态数字孪生决策支持-4664","10.1016\u002Fj.ecolmodel.2026.111867",{"doi":178,"openalex_id":180,"authors":181,"venue":149,"cited_by_count":14,"oa_url":188,"card":189,"direction":55,"ingested_from":56},"W7221174270",[182,185],{"name":183,"orcid":184},"Anna M. Davison","https:\u002F\u002Forcid.org\u002F0000-0003-4249-3424",{"name":186,"orcid":187},"Koen de Koning","https:\u002F\u002Forcid.org\u002F0000-0002-2586-0184","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0304380026003947\u002Fpdf",{"tldr":190,"method":191,"finding":192,"direction":140,"opportunity":193},"论文主张生态数字孪生应转向决策支持，通过共创整合终端用户与社会政治背景。","基于跨学科研究经验，提出共创方法及最佳实践建议。","生态数字孪生需从技术开发转向决策整合，共创是关键路径。","可研究农业数字孪生中终端用户参与机制及社会政治因素对决策采纳的影响。","2026-10-11T23:30:13.457966Z",{"id":196,"title":197,"url":198,"summary":199,"summary_zh":200,"content":8,"source_name":201,"source_url":198,"published_at":202,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":203,"score_detail":204,"sources":207,"tags":209,"primary_topic":8,"secondary_topics":214,"classification":215,"search_phrases":246,"slug":249,"view_count":14,"doi":250,"paper":251,"created_at":266},4348,"Soil and Water Conservation Mechanism in Oil Palm Plantations: A Review of Best Management Practices and Decision Support Strategies","https:\u002F\u002Fdoi.org\u002F10.37394\u002F232015.2026.22.93","Soil and water conservation on oil palm plantation is increasingly considered as a glimmer of hope for the future sustainability of land functionality and environment. Appropriate management practices and informed decision-making frameworks thus have a strong influence on conservation outcomes. This study aims to systematically identify, categorize, synthesize and quantitatively aggregate peer-reviewed evidence regarding soil and water conservation mechanisms in oil palm plantations, focusing on best management practice strategies and decision support. This study uses Systematic Litigation Review (SLR) the Scopus database is used as a reference in searching scientific publication. A keyword-based structured search was used to identify peer-reviewed articles published from 2020 to 2025 and subsequent screening in sequence based on relevance and language. Thirty-eight articles met all the selection criteria for analysis. Then we extracted data and analyzed it using thematic synthesis with descriptive quantitative aggregation of reported metrics (soil loss, SOC change, runoff reduction, or yield response). The results show six main interrelated themes: control of soil erosion; soil fertility and organic matter management; conservation of water and hydrological regulation; integrated land use and landscape management; agronomic best methods practices; and support for decision-making processes. Quantitative synthesis show that cover-based and structural BMPs decrease soil loss by 50–80%, organic amendments increase SOC by 10–35% and integrated water management decreases runoff by 20–60% across regions reported.","油棕种植园的水土保持日益被视为实现土地功能与环境未来可持续性的一线希望。因此，适当的管理实践和基于信息的决策框架对保护成效具有重要影响。本研究旨在系统识别、分类、综合并定量汇总关于油棕种植园水土保持机制的同行评审证据，重点关注最佳管理实践策略与决策支持。本研究采用系统性文献综述（SLR），以Scopus数据库作为科学出版物检索的参考依据。通过基于关键词的结构化检索，识别2020年至2025年发表的同行评审文章，并依据相关性和语言依次进行筛选。共有38篇文章符合所有分析筛选标准。随后，我们提取数据并采用主题综合法进行分析，同时对所报告指标（土壤流失量、土壤有机碳变化、径流减少量或产量响应）进行描述性定量汇总。结果显示六个主要且相互关联的主题：土壤侵蚀控制；土壤肥力与有机质管理；水资源保护与水文调节；综合土地利用与景观管理；农艺最佳方法实践；以及决策过程支持。定量综合表明，在所报告的各区域中，基于覆盖和工程性最佳管理实践（BMPs）使土壤流失减少50%–80%，有机改良剂使土壤有机碳（SOC）增加10%–35%，综合水资源管理使径流减少20%–60%。","WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT","2026-10-05T00:00:00Z",63,{"impact":71,"substance":153,"depth":205,"authority":32,"freshness":59,"relevant":60,"comment":206},17,"系统综述量化了油棕园水土保持措施效果，对热带农业可持续管理有参考价值，但属细分领域研究，公共影响有限。",[208],{"name":201,"url":198},[210,211,20,212,213],"保护性耕作","土壤有机碳","水土保持","油棕种植",[],{"status":25,"locked":13,"version":26,"method":27,"evidence":216},{"candidates":217,"agricultural_evidence":13,"reason":38},[218,225,229,235,241],{"code":219,"score":73,"supported":33,"title":220,"abstract":222,"tags":224},"H2",[221],"soil",[223,221],"土壤",[211],{"code":31,"score":32,"supported":33,"title":226,"abstract":227,"tags":228},[35],[35],[20],{"code":230,"score":231,"supported":33,"title":232,"abstract":233,"tags":234},"H6",4,[],[212],[212],{"code":236,"score":114,"supported":33,"title":237,"abstract":238,"tags":240},"H3",[],[239],"水资源",[],{"code":242,"score":60,"supported":13,"title":243,"abstract":244,"tags":245},"H8",[],[],[210],[247,248],"油棕种植园 水土保持","油棕 最佳管理实践","油棕种植园水土保持-4348","10.37394\u002F232015.2026.22.93",{"doi":250,"openalex_id":252,"authors":253,"venue":201,"cited_by_count":14,"oa_url":259,"card":260,"direction":55,"ingested_from":56},"W7220407703",[254,257],{"name":255,"orcid":256},"Loso Judijanto","https:\u002F\u002Forcid.org\u002F0009-0007-7766-0647",{"name":258,"orcid":8},"Sri Nurhayati","https:\u002F\u002Fwseas.com\u002Fjournals\u002Fead\u002F2026\u002Fb885115-041(2026).pdf",{"tldr":261,"method":262,"finding":263,"direction":264,"opportunity":265},"系统综述油棕园水土保持机制，归纳最佳管理实践与决策支持策略。","系统文献综述，检索Scopus 2020-2025年38篇文献，主题综合与定量汇","覆盖与工程措施减蚀50-80%，有机改良增碳10-35%，综合水管理减径流20-60%。","农业绿色发展与碳","可构建面向油棕园的水土保持决策支持系统，融合多源数据与模型，填补热带种植园智能管理空白。","2026-10-07T23:30:11.425576Z",{"id":268,"title":269,"url":270,"summary":271,"summary_zh":272,"content":8,"source_name":273,"source_url":270,"published_at":202,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":274,"score_detail":275,"sources":278,"tags":280,"primary_topic":285,"secondary_topics":290,"classification":291,"search_phrases":324,"slug":327,"view_count":14,"doi":328,"paper":329,"created_at":340},4324,"Holistic Modeling Approaches for Supporting Sustainability Transitions","https:\u002F\u002Fdoi.org\u002F10.48565\u002Fbonndoc-1000","Agricultural and environmental decisions in agroecological systems are made under profound uncertainty, with complex trade-offs between productivity, ecological integrity and human well-being. This cumulative habilitation thesis brings together 32 peer-reviewed studies that develop and apply holistic modeling approaches to support such decisions and, more broadly, sustainability transitions. The first part advances decision analytical methods in agroecology. Structured decision models, Bayesian networks and Monte Carlo simulations, informed by expert-elicited probabilities, are used to evaluate interventions under incomplete information. Applications span agroforestry adoption and carbon offset schemes, horticultural management strategies, water resource management, flood-based farming systems, agricultural policy and household nutrition, and climate change adaptation and mitigation, with case studies in Africa, Asia, Latin America and Europe. These models identify key trade-offs, risks and leverage points, and value-of-information analyses show where further measurements would most improve decisions. The second part advances methods in transdisciplinary research. It integrates participatory approaches, stakeholder engagement, local and Indigenous knowledge, and holistic sustainability assessment frameworks to co-create context-specific solutions and to bridge science, policy and practice. Together, the studies show that combining probabilistic modeling with participatory processes produces decision support that is both scientifically rigorous and practically relevant. The thesis concludes with implications for policy and with future research directions, including hybrid models that combine expert knowledge with emerging data, multi-criteria trade-off assessment, and the scaling of agroecological practices.","农业生态系统中的农业与环境决策是在深刻的不确定性下作出的， productivity）、生态完整性与人类福祉之间存在复杂的权衡。这本累积性资格论文汇集了32项同行评审研究，这些研究开发并应用整体性建模方法来支持此类决策，并在更广泛意义上支持可持续性转型。第一部分推进了农业生态学中的决策分析方法。结构化决策模型、贝叶斯网络和蒙特卡洛模拟，结合专家引出的概率信息，被用于在不完全信息下评估干预措施。应用范围涵盖农林复合经营采纳与碳补偿方案、园艺管理策略、水资源管理、洪水-based耕作系统、农业政策与家庭营养，以及气候变化适应与减缓，案例研究遍及非洲、亚洲、拉丁美洲和欧洲。这些模型识别了关键权衡、风险和杠杆点，信息价值分析则揭示了进一步的测量在哪些方面最能改善决策。第二部分推进了跨学科研究的方法。它整合了参与式方法、利益相关者参与、地方与原住民知识，以及整体可持续性评估框架，以共同创造情境特定的解决方案，并弥合科学、政策与实践之间的鸿沟。总体而言，这些研究表明，将概率建模与参与式过程相结合，能够产生既科学严谨又具有实际相关性的决策支持。论文最后提出了政策启示和未来研究方向，包括将专家知识与新兴数据相结合的混合模型、多标准权衡评估，以及农业生态实践的规模化推广。","bonndoc (University of Bonn)",74,{"impact":32,"substance":276,"depth":154,"authority":72,"freshness":71,"relevant":60,"comment":277},22,"波恩大学系统综述32项同行评审研究，方法学扎实但偏理论，对国内农业信息化实践的直接指导有限。",[279],{"name":273,"url":270},[20,281,282,283,284],"农业生态","气候变化适应","贝叶斯网络","跨学科研究",{"code":286,"slug":287,"name":288,"path":289,"parent_code":8},"H","environment","资源环境与气候变化","\u002Ftopic\u002Fenvironment",[],{"status":292,"locked":13,"version":26,"method":27,"evidence":293},"partial",{"candidates":294,"agricultural_evidence":33,"reason":323},[295,300,307,312,319],{"code":230,"score":94,"supported":33,"title":296,"abstract":297,"tags":299},[],[281,298],"agroecology",[281],{"code":301,"score":94,"supported":33,"title":302,"abstract":303,"tags":306},"H7",[],[304,305],"气候变化","climate change",[282],{"code":236,"score":59,"supported":33,"title":308,"abstract":309,"tags":311},[],[239,310],"water resource",[],{"code":313,"score":59,"supported":33,"title":314,"abstract":315,"tags":318},"J1",[],[316,317],"农业政策","agricultural policy",[],{"code":31,"score":231,"supported":33,"title":320,"abstract":321,"tags":322},[],[35],[20],"一级领域明确，二级方向需要细分",[325,326],"波恩大学 农业生态 建模","参与式研究 可持续转型","波恩大学农业生态建模-4324","10.48565\u002Fbonndoc-1000",{"doi":328,"openalex_id":330,"authors":331,"venue":273,"cited_by_count":14,"oa_url":270,"card":335,"direction":140,"ingested_from":56},"W7220376706",[332],{"name":333,"orcid":334},"Cory Whitney","https:\u002F\u002Forcid.org\u002F0000-0003-4988-4583",{"tldr":336,"method":337,"finding":338,"direction":140,"opportunity":339},"综合32项研究，用整体建模方法支持农业生态系统的可持续转型决策。","贝叶斯网络、蒙特卡洛模拟、结构化决策模型与参与式方法结合。","概率建模与参与式过程结合可产出科学严谨且实用的决策支持。","可探索专家知识与新兴数据融合的混合模型，及多准则权衡评估的规模化应用。","2026-10-06T23:30:43.643777Z",{"id":342,"title":343,"url":344,"summary":345,"summary_zh":346,"content":8,"source_name":347,"source_url":344,"published_at":348,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":349,"score_detail":350,"sources":352,"tags":354,"primary_topic":358,"secondary_topics":363,"classification":364,"search_phrases":387,"slug":390,"view_count":114,"doi":391,"paper":392,"created_at":412},4219,"Cognitive Causal Modeling of Blockchain Adoption in Agri-Food Supply Chains: A Fuzzy-DEMATEL Approach","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12559-026-10660-0","Background \u002F Introduction: Blockchain can improve agri-food supply-chain transparency, but adoption decisions are cognitively complex because managers judge interdependent criteria under uncertainty. This study frames adoption as cognitive causal decision modeling, aligning with cognitive computation through expert judgment, linguistic uncertainty, causal reasoning, and explainable decision support. Methods: We applied Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to judgments from 20 experts. Eight technology-adoption criteria were modeled using triangular fuzzy numbers, and an impact relationship map was used to classify criteria by outgoing influence (R), incoming influence (C), prominence (R + C), and net causality (R − C). Results: Smart Contracts showed the strongest net causal influence (R = 3.46; R − C = + 0.78). Food Traceability was the most prominent criterion (R + C = 6.40) and the most influenced by other criteria (C = 3.17). Smart Contracts, Payment Transactions, Food Traceability, Fraud Prevention, and Secure Storage were net causes, whereas Food Waste Prevention, Carbon Emission Detection, and Power Consumption were net effects. Sensitivity analysis confirmed a stable cause\u002Feffect partition across threshold and prominence-cutoff variation, with Fraud Prevention the only criterion whose sign reverses at the lower fuzzy bound. Payment Transactions and Secure Storage sit close to the core-driving boundary. Conclusions: The findings support an explainable prioritization logic: transactional and information-security capabilities should be addressed before downstream sustainability outcomes. Because the evidence is expert-elicited rather than longitudinal field performance data, the results should be interpreted as structured decision-support guidance.","背景\u002F引言：区块链可以提高农业食品供应链的透明度，但其采纳决策在认知上较为复杂，因为管理者需要在不确定性下判断相互依赖的标准。本研究将采纳行为界定为认知因果决策建模，通过专家判断、语言不确定性、因果推理和可解释决策支持与认知计算相契合。方法：我们采用模糊决策试验与评价实验室方法（Fuzzy Decision-Making Trial and Evaluation Laboratory，Fuzzy-DEMATEL）对20位专家的判断进行分析。使用三角模糊数对八项技术采纳标准进行建模，并利用影响关系图按输出影响（R）、输入影响（C）、中心度（R + C）和净因果性（R − C）对标准进行分类。结果：智能合约表现出最强的净因果影响（R = 3.46；R − C = + 0.78）。食品追溯是最突出的标准（R + C = 6.40），也是受其他标准影响最大的标准（C = 3.17）。智能合约、支付交易、食品追溯、欺诈预防和安全存储为净原因，而食品浪费预防、碳排放检测和电力消耗为净结果。敏感性分析证实，在阈值和中心度截断值变化下，原因\u002F结果划分保持稳定，欺诈预防是唯一在较低模糊边界下符号发生反转的标准。支付交易和安全存储接近核心驱动边界。结论：研究结果支持一种可解释的优先排序逻辑：交易和信息安全能力应先于下游可持续性结果加以处理。由于证据来自专家 elicitation 而非纵向实地绩效数据，结果应被解释为结构化的决策支持指导。","Cognitive Computation","2026-10-02T00:00:00Z",71,{"impact":32,"substance":153,"depth":205,"authority":72,"freshness":71,"relevant":60,"comment":351},"核心期刊论文，用模糊DEMATEL方法对20位专家判断建模，识别智能合约与食品溯源为区块链采纳的关键驱动因素，方法新颖、结论有决策参考价值，但属专家主观判断而非实地数据，产业影响偏细分领域。",[353],{"name":347,"url":344},[78,355,356,357,20],"农业供应链","农产品溯源","区块链",{"code":359,"slug":360,"name":361,"path":362,"parent_code":286},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon",[],{"status":90,"locked":13,"version":26,"method":27,"evidence":365},{"candidates":366,"agricultural_evidence":33},[367,373,379,383],{"code":359,"score":59,"supported":33,"title":368,"abstract":369,"tags":372},[],[370,371],"碳排放","carbon emission",[],{"code":374,"score":231,"supported":33,"title":375,"abstract":376,"tags":378},"E4",[],[377],"food traceability",[356],{"code":31,"score":231,"supported":33,"title":380,"abstract":381,"tags":382},[],[35],[20],{"code":120,"score":60,"supported":13,"title":384,"abstract":385,"tags":386},[],[],[78],[388,389],"区块链 农产品供应链 溯源","Fuzzy-DEMATEL 区块链","区块链农产品供应链溯源-4219","10.1007\u002Fs12559-026-10660-0",{"doi":391,"openalex_id":393,"authors":394,"venue":347,"cited_by_count":14,"oa_url":406,"card":407,"direction":55,"ingested_from":56},"W7216251074",[395,398,401,404],{"name":396,"orcid":397},"Ali Ala","https:\u002F\u002Forcid.org\u002F0000-0003-4552-4732",{"name":399,"orcid":400},"Behnam Malmir","https:\u002F\u002Forcid.org\u002F0000-0003-1771-9751",{"name":402,"orcid":403},"Hamed Baziyad","https:\u002F\u002Forcid.org\u002F0000-0002-5770-7766",{"name":405,"orcid":8},"Vladimir Simic","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs12559-026-10660-0.pdf",{"tldr":408,"method":409,"finding":410,"direction":140,"opportunity":411},"用模糊DEMATEL对20位专家判断建模，分析农业食品供应链区块链采纳的因果优先级。","模糊DEMATEL、三角模糊数、20位专家判断、敏感性分析","智能合约净因果影响最强，食品溯源最突出；交易与信息安全能力应先于可持续性结果。","可结合纵向田间绩效数据验证专家因果结论，并研究交易安全能力向碳减排等可持续结果的传导机制。","2026-10-05T23:30:12.085269Z",{"id":414,"title":415,"url":416,"summary":417,"summary_zh":418,"content":8,"source_name":419,"source_url":416,"published_at":420,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":421,"score_detail":422,"sources":425,"tags":427,"primary_topic":429,"secondary_topics":433,"classification":434,"search_phrases":461,"slug":464,"view_count":43,"doi":465,"paper":466,"created_at":486},3881,"A Human-Centered Machine Learning Dashboard for Real-Time Smart Farming Decision Support","https:\u002F\u002Fdoi.org\u002F10.68012\u002Fshem.v2i2.302","The integration of machine learning (ML) into precision agriculture has advanced predictive accuracy for tasks such as crop monitoring, irrigation scheduling, and yield estimation. However, many existing IoT-based smart farming systems remain technically driven, offering limited attention to how farmers and field operators actually interact with and interpret model outputs. This gap often results in low adoption rates, as complex predictions fail to translate into actionable, trustworthy decisions for end users. This study proposes a human-centered machine learning dashboard designed to bridge predictive modeling with real-time, farmer-friendly decision support. The system integrates IoT sensor data streams with ML-based prediction modules, presented through an interactive, usability-tested interface that emphasizes clarity, accessibility, and interpretability over raw technical complexity. A working prototype was developed and evaluated using both quantitative usability metrics (e.g., task completion time, System Usability Scale scores) and qualitative feedback from target users to assess the dashboard's effectiveness in supporting field-level decisions. The proposed system architecture, dashboard interface, and underlying ML pipeline are implemented as open and reproducible source code, enabling replication and adaptation across similar smart farming contexts. Results indicate that the human-centered design significantly improves users' comprehension of model outputs and their confidence in acting on system recommendations, without compromising predictive performance. This research contributes a practical framework for designing machine intelligence systems that prioritize end-user experience alongside technical accuracy, offering implications for the broader development of human-centered AI in agricultural and IoT-driven decision support environments.","机器学习（ML）在精准农业中的融合提升了作物监测、灌溉调度和产量估算等任务的预测准确性。然而，许多现有的基于物联网的智慧农业系统仍然以技术驱动为主，对农民和田间操作人员实际如何与模型输出交互并加以解读关注有限。这一差距往往导致采用率偏低，因为复杂的预测无法转化为最终用户可操作、可信赖的决策。本研究提出了一种以人为中心的机器学习仪表盘，旨在将预测建模与实时、面向农民的决策支持相衔接。该系统将物联网传感器数据流与基于机器学习的预测模块相集成，并通过一个经过可用性测试的交互式界面呈现，强调清晰性、可及性和可解释性，而非原始的技术复杂性。我们开发了一个可运行的原型，并使用定量可用性指标（如任务完成时间、系统可用性量表评分）和来自目标用户的定性反馈进行评估，以考察该仪表盘在支持田间决策方面的有效性。所提出的系统架构、仪表盘界面和底层机器学习流水线均以开放且可复现的源代码形式实现，便于在类似的智慧农业场景中复制和适配。结果表明，以人为中心的设计显著提升了用户对模型输出的理解以及依据系统建议采取行动的信心，同时未损害预测性能。本研究为设计在技术准确性的同时优先考虑最终用户体验的机器智能系统提供了一个实用框架，对农业及物联网驱动的决策支持环境中以人为中心的人工智能的更广泛发展具有启示意义。","Smart Human-centered Emerging Research in Machine Intelligence","2026-09-30T00:00:00Z",64,{"impact":32,"substance":154,"depth":423,"authority":12,"freshness":71,"relevant":60,"comment":424},16,"提出以人为本的机器学习仪表盘，兼顾可用性与预测性能，并开源实现，对智慧农业落地有参考价值。",[426],{"name":419,"url":416},[78,79,117,20,428],"人机交互",{"code":31,"slug":430,"name":431,"path":432,"parent_code":87},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[],{"status":90,"locked":13,"version":26,"method":27,"evidence":435},{"candidates":436,"agricultural_evidence":33},[437,444,450,455],{"code":31,"score":438,"supported":33,"title":439,"abstract":441,"tags":443},27,[440,35],"machine learning",[442,440,35],"机器学习",[79,20],{"code":120,"score":12,"supported":33,"title":445,"abstract":446,"tags":449},[],[78,447,448],"精准农业","precision agriculture",[78],{"code":113,"score":94,"supported":33,"title":451,"abstract":452,"tags":454},[],[117,453],"IoT",[117],{"code":236,"score":59,"supported":33,"title":456,"abstract":457,"tags":460},[],[458,459],"灌溉","irrigation",[],[462,463],"农业人工智能 人机交互 决策支持 智慧农业","农业人工智能 人机交互","农业人工智能人机交互决策支持智慧农业-3881","10.68012\u002Fshem.v2i2.302",{"doi":465,"openalex_id":467,"authors":468,"venue":419,"cited_by_count":14,"oa_url":416,"card":481,"direction":55,"ingested_from":56},"W7214922384",[469,472,474,476,478],{"name":470,"orcid":471},"Adam Faturahman","https:\u002F\u002Forcid.org\u002F0000-0001-9727-9092",{"name":473,"orcid":8},"James Williams",{"name":475,"orcid":8},"Evelyn Anderson",{"name":477,"orcid":8},"Goh Yao",{"name":479,"orcid":480},"Muhammad Rifat Syauqy","https:\u002F\u002Forcid.org\u002F0009-0001-4582-5693",{"tldr":482,"method":483,"finding":484,"direction":55,"opportunity":485},"提出以人为中心的机器学习仪表盘，融合物联网与预测模型，为农户提供实时可解释的决策支持。","集成物联网传感器数据流与机器学习预测模块，开发交互式仪表盘，并用SUS量表和用户","以人为中心的设计显著提升用户对模型输出的理解与采纳信心，且不牺牲预测性能。","可探索不同作物、地区和文化背景下农户对可解释AI界面的差异化需求与长期采纳效果。","2026-10-01T23:30:09.481397Z"]