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118 results for “Data-driven”
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Research ArticleOpen accessPhrase in the titlePredictive Analytics and Procurement Visibility: A Big-Data-Driven Approach to Customer Satisfaction in Supply Chain ManagementDevendra Nath Pathak, Rakesh Kumar Yadav, Hitendra SinghIn the current dynamic and consumer driven market environment, supply chains need to move out of reactive to the proactive ecosystems. One of the most urgent requirements is increasing procurement visibility and the development of better order planning for the inventory to meet the products’ demand with continued high customer satisfaction. This paper is an agenda of big-data-driven predictive analytics … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,442 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleLeveraging Transformer Model for Data-Driven Requirement Engineering: A Case Study of NLP4RE E-Commerce Business Apps in Malaysia and IndonesiaDevi Yurisca Bernanda, Dayang Norhayati Abang Jawawi, Shahliza Abd Halim et al.Data-Driven Requirement Engineering (DDRE) marks a departure from conventional methods, embracing dynamic, user-centric strategies with the help of machine learning and artificial intelligence. As software systems grow more intricate and demand adaptability, a continuous software engineering approach becomes crucial. However, this shift poses challenges in handling data inconsistencies during the elicitation process, leading to software development shortcomings. This study tackles … …Journal of Computer Science, Vol. 20, Issue 11 · 2 Oct 2024 · 5,131 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleData-Driven Forecasting Schemes: Evaluation and ApplicationsJosip Vrbanek Jr, Wilson WangA reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,565 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,136 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA User-Driven Association Rule Mining Based on Templates for Multi-Relational DataCarlos Roberto Valêncio, Guilherme Henrique Morais, Márcio Zamboti Fortes et al.Data mining algorithms to find association rules are an important tool to extract knowledge from databases. However, these algorithms produce an enormous amount of rules, many of which could be redundant or irrelevant for a specific decision-making process. Also, the use of previous knowledge and hypothesis are not considered by these algorithms. On the other hand, most existing data mining … …Journal of Computer Science, Vol. 14, Issue 11 · 8 Nov 2018 · 7,442 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHealthcare Driven by Big Data AnalyticsCheryl Ann Alexander, Lidong WangText messages and social network posts are often included in big data and are frequently invaluable sources of health data. When machine learning or data mining is used, it is important to perform an automatic process for integrating all available and related health data. Artificial Neural Network (ANN) is one of the machine learning methods flexible in using algorithms to … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 28 Sep 2018 · 7,398 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleBig Data Driven Supply Chain Management and Business AdministrationLidong Wang, Cheryl Ann AlexanderBig Data helps improve visibility throughout the supply chain, provides an integrated view of operational performance and customer interaction and gives businesses real-time insights that help make critical decisions. Big Data also has a potential to yield new management principles. This paper introduces the Big Data concept, its characteristics and some major issues of Big Data in supply chain management … …American Journal of Economics and Business Administration, Vol. 7, Issue 2 · 20 Jun 2015 · 8,662 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCombined Pattern Mining for D3M Using FuzzyS. S. Dhenakaran, S. MaheswariMany algorithms and models were developed but the findings are not actionable and lack of soft power while solving the complex problems. Domain Driven Data mining is used a major efforts to promote the action ability of the knowledge discovery in the real world smart decision making. Combined mining is one of the common methods for analyzing complex data for … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 1 Nov 2013 · 6,750 accessesView PDFCite
Research ArticleOpen accessIn the keywordsWeighting Spatial Information in GIS for Copper Mining ExplorationFarhad Hosseinali, Ali Asghar AlesheikhExploration of new mines is vitally important for human life. Geospatial Information Systems (GIS) can be effectively used in the gathering, weighting, analyzing and presenting spatial and attribute information to facilitate the mine exploration process. The success of mine exploration largely depends on: the identification of governing factors, the determination of their impacts and the selection of suitable models to … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 8,603 accessesView PDFCite