Research on electronic decision system for effective data visualization and analysis process. (March 2022)

• Record Type: Journal Article
• Authors: jiao, PengJian
• Is Part Of: Computers & electrical engineering. Volume 98(2022)
• Publication Date: 2022-03
• Subjects: Artificial neural network -- Big data analytics -- Decision making -- Electronic decision system -- Data visualization -- Leaders -- Managers -- Effective data -- Analysis process; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107737
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Today, more leaders, managers, and directors can decide, even though they cannot decide for every situation. When decisions are scattered and unstructured, decisions become complicated and so that a single decision-maker based on expertise alone cannot address them adequately. This research proposes the Electronic Decision System (EDS) for effective data visualization and analysis process. EDS helps to decide during a complicated situation using Big Data Analytics-based Artificial Neural Network Framework (BDA-ANNF). The BDA-ANNF collects and analyses the data provided, and Artificial Neural Network (ANN) is used to predict and take accurate decisions in every complicated situation. These systems allow decision-makers to understand the market, direct and indirect climate, analyze the numerous trade-offs in the sector, evaluate costs linked to the various choices for decision-making, and eventually help people improve their decision-making outcome. EDS's approaches and techniques share one key challenge that must successfully provide consumers and policymakers with an appropriate and understandable simulation solution. The finding indicates that the BDA-ANNF decides the complicated situation up to the accuracy rate of 95.23%, which is not attainable by existing methods, and the error rate is 4.77%.