Research on electronic decision system for effective data visualization and analysis process. (March 2022) - jiao, PengJian
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%.