this paper introduces a technique for controlling a class of uncertain chaotic systems using an adaptive fuzzy proportional-integrator-derivative (pid) controller with h∞ tracking performance. the purpose of this work is to achieve optimal tracking performance of the controller using backtracking search algorithm (bsa). bsa, which is a novel heuristic algorithm, has an easy structure with singl...

Recently huge amount of data is available in the field of medicine that helps the doctors in diagnosing diseases when analysed. Data mining techniques can be applied to these medical data to extract knowledge so that disease prediction becomes accurate and easier. In this work, cardiotocogram (CTG) data is analysed using Support Vector Machine (SVM) for predicting fetal risk. Opposition based f...

Due to dynamic and uncertain nature of many optimisation problems in real-world, the applied algorithm in this environment must be able to continuously track the changing optima over time. In this paper, we report a novel speciation-based firefly algorithm for dynamic optimisation, which improved its performance by employing prior landscape historical information. The proposed algorithm, namely...

For the uncertain factors in fire allocation process of air and missile defense problem, uncertainty theory is used to deal with an multi-objective dynamic weapon target assignment model proposed. In order above model, a evolutionary algorithm based on decomposition proposed, which adds displacement mechanism firefly uniformly randomly adaptive weights mechanism. Then, simulation results show t...

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining th...

The problem of resources under the environment of cloud computing has always been the focus of research. In this paper, the Artificial Firefly Algorithm is studied, on the basis of which the chaos algorithm is introduced to improve the algorithm with regard to the problem of the subsequent search and optimization precision deficiency cause by the lack of initialization of firefly position in th...

In this paper, a novel hybrid optimization algorithm, which combines a firefly algorithms and Artificial Bee Colony algorithm (FFAABC), is proposed for solving the economic power dispatch (EPD) problem. The hybrid algorithm is structured with two stages. The first stage uses the search by firefly algorithm (FFA) and second stage is a search with Artificial Bee Colony algorithm (ABC). The hybrid...

Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with diverse applications. In this paper, we will briefly review the fundamentals of firefly algorithm together with a selection of recent publications. Then, we d...

Bio-inspired algorithms become among the most powerful algorithms for optimization. In this paper, we intend to provide one of the recent bio-inspired metaheuristic which is the Firefly Algorithm (FF) to optimize power dispatching. For evaluation, we adapt the particle swarm optimization to the problem in the same way as the firefly algorithm. The application is done in an IEEE-14 and on two th...