Journal of Applied Data Sciences
Vol 3, No 2: MAY 2022

Elevator Group Scheduling by Improved Dayan Particle Swarm Algorithm in Computer Cloud Computing Environment

Jie Yu (Fudan University, Shanghai, China)
Bo Hu (Fudan University, Shanghai, China)



Article Info

Publish Date
24 May 2022

Abstract

The world is entering the era of cloud computing. Due to the rapid development of computer technology, as the core content of elevator transportation technology, elevator group control dispatching systems and group intelligent algorithms will have a wide range of application prospects due to their significant advantages. The purpose of this paper is to study the elevator group scheduling problem of the improved Dayan particle swarm algorithm in the computer cloud computing environment.This article first summarizes the research status of elevator group control technology and algorithms, and then analyzes and studies the basic theory of cloud computing task scheduling. Combined with the improved Dayan particle swarm algorithm, the elevator prediction model is established. This paper systematically expounds the theory and algorithm principle of the basic particle swarm algorithm, and analyzes the Dayan particle swarm algorithm on this basis. In this paper, the experimental research is carried out by comparing the two algorithms on the simulation software. Research shows that the improved Dayan particle swarm algorithm has better scheduling performance than the traditional basic particle swarm algorithm.

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Journal Info

Abbrev

JADS

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes ...