A modified particle swarm optimization algorithm based on velocity updating mechanism

Artificial Bee Colony (ABC) algorithm is a novel bio-inspired swarm intelligence approach which is competitive with other population-based algorithms and has the advantage of using fewer control parameters. However, basic ABC is easy to be prematurely convergent and be trapped into local optimum. In the later iteration, algorithm has low convergent speed and population diversity seriously decreases. In this paper, Gaussian mutation and chaos disturbance are introduced into ABC to overcome the shortcomings above. Applications of improved ABC algorithm on four benchmark optimization functions show marked improvement in performance over the basic ABC.

An improved artificial bee colony algorithm based on gaussian mutation and chaos disturbance

Inspired by sensor coverage density and matching & preserving strategy, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm which is designed to optimize bridge sensor placement. We use dynamic random coverage coding method to initialize colony to ensure the diversity and effectiveness. In addition, we randomly select the factors with lower trust value to search and evolve after food source being matched in order that the relatively high trust point factor is retained in the exploitation of food sources, which reduces the blindness of searching and improves the efficiency of convergence and the accuracy of the algorithm. According to the analysis of the modal data of the Ha-Qi long span railway bridge, the results show that IABC algorithm has faster convergence rate and better global search ability when solving the optimal placement problem of bridge sensor. The final analysis results also indicate that the IABC’s solution accuracy is 76.45% higher than that of the ABC algorithm, and the solution stability is improved by 86.23%. The final sensor placement mostly covers the sensitive monitoring points of the bridge structure and, in this way, the IABC algorithm is suitable for solving the optimal placement problem of large bridge and other structures.

Improved ABC Algorithm Optimizing the Bridge Sensor Placement.

Most optimization problems in real life applications are often highly nonlinear. Only global optimization algorithms should be used to obtain optimal solutions. This paper introduces a new nature-inspired metaheuristic optimization algorithm, called Fast Artificial Fish Swarm Algorithm (FAFSA) for optimization and job scheduling. The basic idea of AFSA is to tradition of the behaviors of fish such as preying, swarming, and following with local fish of individual optimization of global reach.

/pdf/fafsa-fast-artificial-fish-swarm-algorithm-4l88hv2iz2.pdf

FAFSA: Fast Artificial Fish Swarm Algorithm

Methods for edible oil quality detection mainly have conductivity and peroxide acid value, but as for currently blending edible detection, the effect of these methods is not satisfied. In this study, we propose a cluster algorithm based on artificial fish swarm improvement to detect edible oil by voltammetric electronic tongue. It can optimize the cluster centers value and the initial value. The results show that this is significant to classification and detection of edible oil using the artificial fish swarm cluster algorithm in voltammetric electronic tongue system.

/pdf/application-of-electronic-tongue-in-edible-oil-detection-22vikzglif.pdf

Application of Electronic Tongue in Edible Oil Detection with Cluster Algorithm based on Artificial Fish Swarm Improvement

An improved algorithm (AFSA-IWO) was developed based on the artificial fish swarm algorithm (AFSA) and invasive weed optimization (IWO). It introduces IWO, and improves its mechanism of the competitive exclusion to meet practical application. Convergence analysis was performed with some typical benchmark test functions and comparison was made with AFSA. At the same time, it uses the AFSA-IWO to optimize the PID parameters. The results showed that the approach presented better ability in leaping over the local extremum and enhancing local exploration, and can void blind searching in the later evolution period. So it is a global optimization algorithm with good feasibility and high efficiency.

An Improved Artificial Fish Swarm Algorithm and its Application

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Xin Guan

Author Tools

Chat about Author

Papers

An Improved Artificial Fish Swarm Algorithm and its Application