نتایج جستجو برای: swarm intelligence algorithms
تعداد نتایج: 435451 فیلتر نتایج به سال:
In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuz...
Big data is the slightly abstract phase which describes the relationship between the data size and data processing speed in the system. The many new information technologies the big data deliver dramatic cost reduction, substantial improvements in the required time to perform the computing task or new product and service offerings. The several complicated specific and engineering problems can b...
Swarm intelligence algorithms are inherently parallel since different individuals in the swarm perform independent computations at different positions simultaneously. Hence, these algorithms lend themselves well to parallel implementations thereby speeding up the optimization process. FireWorks Algorithm (FWA) is a recently proposed swarm intelligence algorithm for optimization. This work inves...
Swarm intelligence is a research field that models the collective intelligence in swarms of insects or animals. Many algorithms that simulates these models have been proposed in order to solve a wide range of problems. The Artificial Bee Colony algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behaviour of honey bee colonies. In this work, modi...
Designing multi-hop protocols and implementing algorithms for wireless sensor networks (WSNs) is an area of research. The concept of swarm intelligence(SI) presents various protocols suitable for field of WSNs and the intelligence of nature inspired techniques like that of bees proves to be an inspiration for working of nodes in different areas of applications. In this paper, we discuss the rou...
Swarm behavior suggests simple methodologies used by agents of swarm to solve complex problems, which using the other optimsation algorithms such as Genetic Algorithms may not be possible to solve. The basic reason behind this is the group behavior in these algorithms. The distributed control mechanism and simple interactive rules can manage the swarm efficiently and effectively. Flocking behav...
The proposed algorithm in this research is based on the multi-agent particle swarm optimization as a collective intelligence due to the connection between several simple components which enables them to regulate their behavior and relationships with the rest of the group according to certain rules. As a result, self-organizing in collective activities can be seen. Community structure is crucial...
This paper aims at optimizing the parameters involved in stress analysis of perforated plates, in order to achieve the least amount of stress around the square-shaped holes located in a finite isotropic plate using metaheuristic optimization algorithms. Metaheuristics may be classified into three main classes: evolutionary, physics-based, and swarm intelligence algorithms. This research uses Ge...
This paper presents the results of a comparative study of network routing approaches. Recent advances in the field suggest that swarm intelligence may offer a robust, high quality solution. The overall aim of the study was to develop a framework to facilitate the empirical evaluation of a swarm intelligence routing approach compared to a conventional static and dynamic routing approach. This pa...
In the field of economics and business, the ever increasing amount of text documents written in different languages and the ever increasing dependence of people and organisations on such information require effective document retrieval, searching and classification mechanisms. Searching for groups of related documents has an important role in text mining and Document Management Systems. Swarm i...
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