Swarm intelligence deals with natural and arti cial systems composed of many individuals that coordinate using decentralized control and self-organization [1, 2, 5]. The main focus of swarm intelligence research is on the collective behaviour that results from local interactions of individuals with each other and with their environment. There are many examples of natural systems that are studie...

For a decade swarm Intelligence is concerned with the design of intelligent systems by taking inspiration from the collective behaviors of social insects. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and P...

This review paper sets out to explore the question of how future complex engineered systems based upon the swarm intelligence paradigm could be assured for dependability. The paper introduces the new concept of ‘swarm engineering’: a fusion of dependable systems engineering and swarm intelligence. The paper reviews the disciplines and processes conventionally employed to assure the dependabilit...

In this paper, the main aim is to exhibit swarm intelligence power in cloud based scenario. Heterogeneous environment has been configured at server-side network of the whole cloud network. In the proposed system, different types of servers are being used to manage useful assorted atmosphere. Swarm intelligence has been adopted for enhancing the performance of overall system network. Specific lo...

Swarm intelligence describes the ability of groups of social animals and insects to exhibit highly organized and complex problem-solving behaviors that allow the group as a whole to accomplish tasks which are beyond the capabilities of any one of the constituent individuals. This natural phenomenon is the inspiration for swarm intelligence systems, a class of algorithms that utilizes the emerge...

This paper surveys the intersection of two fascinating and increasingly popular domains: swarm intelligence and optimization. Whereas optimization has been popular academic topic for decades, swarm intelligence is relatively new subfield of artificial intelligence which studies the emergent collective intelligence of groups of simple agents. It is based on social behavior that can be observed i...

The research field of swarm intelligence contains various algorithms inspired from the particular survival skills of the creatures in Mother Nature. Many researchers utilize these methods to solve problems in engineering and financial fields. In this review, the concept of four swarm intelligence methods, including Bat Algorithm (BA), Evolved Bat Algorithm (EBA), Cat Swarm Optimization (CSO), a...

Swarm Intelligence is an artificial intelligence discipline which is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviours of social insects and other animal societies. They are characterized by a decentralized way of working that mimics the behaviour of the swarm. Swarm Intelligence is a successful paradigm for the algorithm with comp...

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...

Artificial Neural Network (ANN) has found widespread application in the field of classification. Many domains have benefited with the use of ANN based models over traditional statistical models for their classification and prediction needs. Many techniques have been proposed to arrive at optimal values for parameters of the ANN model to improve its prediction accuracy. This paper compares the i...