Original Elman, which is one of the well-known dynamic recurrent neural network (DRNN), has been improved to easily apply in dynamic systems identification during the past decade. In this paper, a learning algorithm for Original Elman neural networks (ENN) based on modified particle swarm optimization (MPSO), which is a swarm intelligent algorithm (SIA), is presented. MPSO and Elman are hybridi...

Abstract Formation flight of unmanned aerial vehicles (UAVs) utilizes reconfiguration procedures to handle a variety emergencies, such as collision avoidance, malfunctions, fuel savings, and member replacement. As UAVs have limited computing power energy resources, it is necessary optimize the control inputs reduce distance travelled by while reducing costs during formation reconfiguration. In ...

The iterative Fourier transform algorithm (IFTA) is widely used in various optical communication applications based on liquid crystal silicon spatial light modulators. However, the traditional method has many disadvantages, such as a poor effect, an inability to select optimization direction, and failure consider zero padding or phase quantization. Moreover, after years of development, emergenc...

In this article, Hill Climbing (HC) and Estimation of Distribution Algorithm (EDA) are integrated to produce a hybrid intelligent algorithm for design of endlessly Single Mode Photonic Crystal Fibers (SMPCFs) structure with desired properties over the C communication band. In order to analyzing the fiber components, Finite Difference Frequency Domain (FDFD) solver is applied. In addition, a spe...

This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM). Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. The results of this study pr...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

The aim of this study is to present a hybrid algorithm based on two meta-heuristic algorithms named Vibration Damping Optimization (VDO) algorithm and Genetic Algorithm (GA) for solving the stochastic capacitated location-allocation problem. For solving the model more efficiently, the simplex algorithm, stochastic simulation and the proposed hybrid algorithm are integrated to design a powerful ...

Machine learning is a major branch of AI and a main research direction of multi-agent systems (MAS). With the emergence of various new complex systems, agent’s individual ability and the system’s intelligence level are urgently to be improved. Agent learning methods and agent architecture are studied in this paper and a new hybrid intelligent learning algorithm based on multi-agent is proposed....

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid inte...