Social and Business Intelligence Analysis Using PSO

TL;DR

This paper explores the application of particle swarm optimization (PSO) to enhance social and business intelligence analysis, focusing on decision making and management of spatial data within enterprises.

Contribution

It introduces a novel use of PSO for improving business intelligence processes and handling spatial data limitations in SQL Server.

Findings

PSO facilitates social and business intelligence.

Spatial data processing benefits from PSO techniques.

PSO improves decision-making efficiency.

Abstract

The goal of this paper is to elaborate swarm intelligence for business intelligence decision making and the business rules management improvement. .The swarm optimization, which is highly influenced by the behavior of creature, performs in group. The Spatial data is defined as data that is represented by 2D or 3D images. SQL Server supports only 2D images till now. As we know that location is an essential part of any organizational data as well as business data enterprises maintain customer address lists, own property, ship goods from and to warehouses, manage transport flows among their workforce, and perform many other activities. By means to say a lot of spatial data is used and processed by enterprises, organizations and other bodies in order to make the things more visible and self descriptive. From the experiments, we found that PSO is can facilitate the intelligence in social and business behavior.