检索结果-南通市图书馆

Enhancing aquaponics management with IoT-based predictive analytics for efficient information utilization

Information Processing in Agriculture 2019年第3期6卷 375-385页

作者： Divas Karimanzira Thomas Rauschenbach Dept of Surface and Maritime Systems Fraunhofer I0SB-ASTIlmenauAm Vogelherd 5098689 IlmenauGermany

Modern aquaponic systems can be highly successful,but they require intensive monitoring,control and ***,the Automation Pyramid(AP)with its layers of Supervisory Control and Data Acquisition(SCADA),Enterprise Resource Planning(ERP)and Manufacturing Execution System(MES)is applied for process *** cloudbased IoT-based predictive analytics at the fore marsh,it is worth finding out if IoTwill make these technologies obsolete,or they can work together to gain more beneficial *** this paper,we will discuss the enhancement of SCADA,ERP and MES with IoT in aquaponics and likewise how IoT-based predictive analytics can help to get more out of *** example use case of an aquaponics project with five demonstration sites in different geographical locations will be presented to show the benefits of IoT on example predictive analytics *** is the collection of data from the five demonstration sites over IoT to make the models of fish,tomatoes,technical components such as filters used for remote monitoring,predictive remote maintenance and economical optimization of the individual plants *** of the various models,fish and crop growth models,models for econometric optimization were evaluated using Monte Carlo Simulations revealing as expected the superiority of the IoT-based *** analysis suggest that the models are generally tolerant to the temperature coefficient variations of up to 15%and the econometric models tolerated a variation of for example feed ration size for fish of up to 4%and by the energy optimization models a tolerance of up to 14%by variations of solar radiation could be ***,from the analysis made,it can be concluded that MES has several capabilities which cannot be replaced by IoT such as responsiveness to trigger changes on *** act as proxy when there is no case for sensors and reliably ensure correct execution in the aquaponics *** systems can produce unpreced

关键词： Aquaponics Automation pyramid IoT predictive analytics Big Data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

predictive analytics for Project Risk Management Using Machine Learning

引用

Journal of Data Analysis and Information Processing 2024年第4期12卷 566-580页

作者： Sanjay Ramdas Bauskar Chandrakanth Rao Madhavaram Eswar Prasad Galla Janardhana Rao Sunkara Hemanth Kumar Gollangi Shravan Kumar Rajaram Pharmavite LLC Los Angeles CA USA Microsoft Charlotte NC USA AXS Group LLC Los Angeles CA USA TCS Indianapolis IN USA

Risk management is relevant for every project that which seeks to avoid and suppress unanticipated costs, basically calling for pre-emptive action. The current work proposes a new approach for handling risks based on predictive analytics and machine learning (ML) that can work in real-time to help avoid risks and increase project adaptability. The main research aim of the study is to ascertain risk presence in projects by using historical data from previous projects, focusing on important aspects such as time, task time, resources and project results. t-SNE technique applies feature engineering in the reduction of the dimensionality while preserving important structural properties. This process is analysed using measures including recall, F1-score, accuracy and precision measurements. The results demonstrate that the Gradient Boosting Machine (GBM) achieves an impressive 85% accuracy, 82% precision, 85% recall, and 80% F1-score, surpassing previous models. Additionally, predictive analytics achieves a resource utilisation efficiency of 85%, compared to 70% for traditional allocation methods, and a project cost reduction of 10%, double the 5% achieved by traditional approaches. Furthermore, the study indicates that while GBM excels in overall accuracy, Logistic Regression (LR) offers more favourable precision-recall trade-offs, highlighting the importance of model selection in project risk management.

关键词： predictive analytics Project Risk Management Decision-Making Data-Driven Strategies Risk Prediction Machine Learning Historical Data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Leveraging predictive analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

引用

Journal of Computer and Communications 2024年第10期12卷 51-61页

作者： Natalie Nkembuh Department of Communication European International University Paris France

This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.

关键词： predictive analytics Corporate Communications Stakeholder Engagement Crisis Management Machine Learning Data-Driven Strategy Ethical AI Digital Transformation Reputation Management Strategic Communication

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Game Theory Based Model for predictive analytics Using Distributed Position Function

引用

International Journal of Intelligence Science 2024年第1期14卷 22-47页

作者： Mirhossein Mousavi Karimi Shahram Rahimi Department of Computer Science and Engineering Mississippi State University Starkville USA

This paper presents a game theory-based method for predicting the outcomes of negotiation and group decision-making problems. We propose an extension to the BDM model to address problems where actors’ positions are distributed over a position spectrum. We generalize the concept of position in the model to incorporate continuous positions for the actors, enabling them to have more flexibility in defining their targets. We explore different possible functions to study the role of the position function and discuss appropriate distance measures for computing the distance between the positions of actors. To validate the proposed extension, we demonstrate the trustworthiness of our model’s performance and interpretation by replicating the results based on data used in earlier studies.

关键词： Distributed Position Function Game Theory Group Decision Making predictive analytics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Revolutionizing diabetic retinopathy screening and management:The role of artificial intelligence and machine learning

引用

World Journal of Clinical Cases 2025年第5期13卷 1-12页

作者： Mona Mohamed Ibrahim Abdalla Jaiprakash Mohanraj Department of Human Biology School of MedicineInternational Medical UniversityBukit Jalil 57000Kuala LumpurMalaysia

Diabetic retinopathy(DR)remains a leading cause of vision impairment and blindness among individuals with diabetes,necessitating innovative approaches to screening and *** editorial explores the transformative potential of artificial intelligence(AI)and machine learning(ML)in revolutionizing DR *** and ML technologies have demonstrated remarkable advancements in enhancing the accuracy,efficiency,and accessibility of DR screening,helping to overcome barriers to early *** technologies leverage vast datasets to identify patterns and predict disease progression with unprecedented precision,enabling clinicians to make more informed ***,AI-driven solutions hold promise in personalizing management strategies for DR,incorpo-rating predictive analytics to tailor interventions and optimize treatment *** automating routine tasks,AI can reduce the burden on healthcare providers,allowing for a more focused allocation of resources towards complex patient *** review aims to evaluate the current advancements and applic-ations of AI and ML in DR screening,and to discuss the potential of these techno-logies in developing personalized management strategies,ultimately aiming to improve patient outcomes and reduce the global burden of *** integration of AI and ML in DR care represents a paradigm shift,offering a glimpse into the future of ophthalmic healthcare.

关键词： Diabetic retinopathy Artificial intelligence Machine learning Screening Management predictive analytics Personalized medicine

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

SOCIAL MEDIA RESEARCH:A REVIEW

引用

Journal of Systems Science and Systems Engineering 2013年第3期22卷 257-282页

作者： Junjie WU Haoyan SUN Yong TAN School of Economics and Management Beihang University Michael G.Foster School of Business University of Washington

Social media is fundamentally changing the way people communicate, consume and collaborate. It provides companies a new platform to interact with their customers. In academia, there is a surge in research efforts on understanding its effects. This paper aims to provide a review of current status of social media research. We discuss the specific domains in which the impacts of social media have been examined. A brief review of applicable research methodologies and approaches is also provided.

关键词： social media empirical models experimental methods analytical approaches predictive analytics

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity

引用

Computers, Materials & Continua 2020年第4期63卷 537-551页

作者： Xiangao Jiang Megan Coffee Anasse Bari Junzhang Wang Xinyue Jiang Jianping Huang Jichan Shi Jianyi Dai Jing Cai Tianxiao Zhang Zhengxing Wu Guiqing He Yitong Huang Department of Infectious Diseases Wenzhou Central HospitalWenzhou325000China Division of Infectious Diseases and Immunology Department of MedicineNew York UniversityNew YorkUSA Department of Population and Family Health Mailman School of Public HealthColumbia UniversityNew YorkUSA Courant Institute of Mathematical Sciences Computer Science DepartmentNew York UniversityNew YorkUSA Columbia College Columbia UniversityNew YorkUSA Departments of Infectious Diseases Cangnan People’s HospitalWenzhou325800China Department of Gynaecology Wenzhou Central HospitalWenzhou325000China

The virus SARS-CoV2,which causes the Coronavirus disease COVID-19 has become a pandemic and has spread to every inhabited *** the increasing caseload,there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical *** present a first step towards building an artificial intelligence(AI)framework,with predictive analytics(PA)capabilities applied to real patient data,to provide rapid clinical decision-making ***-19 has presented a pressing need as a)clinicians are still developing clinical acumen given the disease’s novelty,and b)resource limitations in a rapidly expanding pandemic require difficult decisions relating to resource *** objectives of this research are:(1)to algorithmically identify the combinations of clinical characteristics of COVID-19 that predict outcomes,and(2)to develop a tool with AI capabilities that will predict patients at risk for more severe illness on initial *** predictive models learn from historical data to help predict specifically who will develop acute respiratory distress syndrome(ARDS),a severe outcome in *** experimental results based on two hospitals in Wenzhou,Zhejang,China identify features most predictive of ARDS in COVID-19 initial presentation which would not have stood out to clinicians.A mild increase in elevated alanine aminotransferase(ALT)(a liver enzyme)),a presence of myalgias(body aches),and an increase in hemoglobin,in this order,are the clinical features,on presentation,that are the most *** two centers’COVID-19 case series symptoms on initial presentation can help predict severe *** models that learned from historical data of patients from two Chinese hospitals achieved 70%to 80%accuracy in predicting severe cases.

关键词： SARS-CoV2 COVID-19 coronavirus infectious diseases artificial intelligence predictive analytics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Reinforcing Artificial Neural Networks through Traditional Machine Learning Algorithms for Robust Classification of Cancer

引用

Computers, Materials & Continua 2023年第5期75卷 4293-4315页

作者： Muhammad Hammad Waseem Malik Sajjad Ahmed Nadeem Ishtiaq Rasool Khan Seong-O-Shim Wajid Aziz Usman Habib Department of Computer Sciences and Information Technology University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Computer Science and AI College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of Computer and Network Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of AI&DS School of ComputingNational University of Computer and Emerging SciencesIslamabad44000Pakistan

Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target ***,improving predictive accuracy is a crucial step for informed *** the healthcare domain,data are available in the form of genetic profiles and clinical characteristics to build prediction models for complex tasks like cancer detection or *** ML algorithms,Artificial Neural Networks(ANNs)are considered the most suitable framework for many classification *** network weights and the activation functions are the two crucial elements in the learning process of an *** weights affect the prediction ability and the convergence efficiency of the *** traditional settings,ANNs assign random weights to the *** research aims to develop a learning system for reliable cancer prediction by initializing more realistic weights computed using a supervised setting instead of random *** proposed learning system uses hybrid and traditional machine learning techniques such as Support Vector Machine(SVM),Linear Discriminant Analysis(LDA),Random Forest(RF),k-Nearest Neighbour(kNN),and ANN to achieve better accuracy in colon and breast cancer *** system computes the confusion matrix-based metrics for traditional and proposed *** proposed framework attains the highest accuracy of 89.24 percent using the colon cancer dataset and 72.20 percent using the breast cancer dataset,which outperforms the other *** results show that the proposed learning system has higher predictive accuracies than conventional classifiers for each dataset,overcoming previous research ***,the proposed framework is of use to predict and classify cancer patients ***,this will facilitate the effective management of cancer patients.

关键词： ANN decision support systems gene-expression data hybrid classification machine learning predictive analytics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI)

引用

Computers, Materials & Continua 2021年第1期66卷 589-602页

作者： Sadaf Qazi Muhammad Usman Azhar Mahmood Aaqif Afzaal Abbasi Muhammad Attique Yunyoung Nam Predicitive analytics Laboratory Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan Department of Software Sejong UniversitySeoul05006Korea Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and *** Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immunization activities,however the coverage is quite low despite the accessibility of free *** study proposes a defaulter prediction model for accurate identification of *** proposed framework classifies defaulters at five different stages:defaulter,partially high,partially medium,partially low,and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization *** machine learning algorithms are applied on Pakistan Demographic and Health Survey(2017–18)*** Perceptron yielded 98.5%accuracy for correctly identifying children who are likely to default from immunization series at different risk stages of being *** this paper,the proposed defaulters’prediction framework is a step forward towards a data-driven approach and provides a set of machine learning techniques to take advantage of predictive ***,predictive analytics can reinforce immunization programs by expediting targeted action to reduce ***,the accurate predictions support targeted messages sent to at-risk parents’and caretakers’consumer devices(e.g.,smartphones)to maximize healthcare outcomes.

关键词： Smart healthcare routine immunization predictive analytics defaulters vaccination machine learning targeted messaging

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Systematic Review Towards Big Data analytics in Social Media

引用

Big Data Mining and analytics 2022年第3期5卷 228-244页

作者： Md.Saifur Rahman Hassan Reza School of Electrical Engineering and Computer Science University of North DakotaGrand ForksND 58202USA

The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 *** new era allows the consumer to directly connect with other individuals,business corporations,and the *** are open to sharing opinions,views,and ideas on any topic in different formats out *** creates the opportunity to make the"Big Social Data"handy by implementing machine learning approaches and social data *** study offers an overview of recent works in social media,data science,and machine learning to gain a wide perspective on social media big data *** explain why social media data are significant elements of the improved data-driven decision-making *** propose and build the"Sunflower Model of Big Data"to define big data and bring it up to date with technology by combining 5 V’s and 10 *** discover the top ten social data analytics to work in the domain of social media platforms.A comprehensive list of relevant statistical/machine learning methods to implement each of these big data analytics is discussed in this work."Text analytics"is the most used analytics in social data analysis to *** create a taxonomy on social media analytics to meet the need and provide a clear ***,techniques,and supporting data type are also discussed in this research *** a result,researchers will have an easier time deciding which social data analytics would best suit their needs.

关键词： big data social media big data analytics social media analytics text analytics image analytics audio analytics video analytics predictive analytics descriptive analytics prescriptive analytics diagnostic analytics

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：