Genetic algorithms (GA) have been widely used to solve water resources system optimization. However, when applying GAs to solve large-scale and complex water reservoir system problems, premature convergence is one of the most frequently encountered difficulties and takes a large number of iterations to reach the global optimal solution and the optimization may get stuck at a local optimum. Ther...

We propose a Nyquist optical time division multiplexing transmission scheme using optical root-Nyquist pulses and an optical correlation receiving technique. This scheme can satisfy the Nyquist criterion for zero inter-symbol interference and an optimum detection to maximize the signal-to-noise ratio. Moreover, the processing speed can exceed the speed limitation of electrical devices. We descr...

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stag...

The activity of a team of autonomous mobile agents formed by identical “robot-like-ant” individuals capable of performing a random walk through an environment that are able to recognize and move different “objects” is modeled. The emergent desired behavior is a distributed sorting and clustering based only on local information and a memory register that records the past objects encountered. An ...

In order to improve the convergence speed and the drawback of easily converging to the local optimum of the standard particle swarm optimization (PSO), two improved PSO algorithms are presented based on the simple particle swarm optimization algorithm without speed attribute. One is introducing differential mutation technology of differential evolution algorithm into the simple PSO algorithm fo...

The shuffled frog leaping algorithm (SFLA) easily falls into local optimum when it solves multioptimum function optimization problem, which impacts the accuracy and convergence speed. Therefore this paper presents grouped SFLA for solving continuous optimization problems combined with the excellent characteristics of cloud model transformation between qualitative and quantitative research. The ...

This paper proposes the current search (CS) metaheuristics conceptualized from the electric current flowing through electric networks for optimization problems with continuous design variables. The CS algorithm possesses two powerful strategies, exploration and exploitation, for searching the global optimum. Based on the stochastic process, the derivatives of the objective function is unnecessa...

In this study, we found that the optimum take-off angle for a long jumper may be predicted by combining the equation for the range of a projectile in free flight with the measured relations between take-off speed, take-off height and take-off angle for the athlete. The prediction method was evaluated using video measurements of three experienced male long jumpers who performed maximum-effort ju...

The low-temperature performance of vertical cavity lasers (VCL’s) is of interest for high-speed data transmission from superconducting and cryogenic semiconductor circuits. Our double-fused 1.5 m lasers employ a strain-compensated InGaAsP/InP multiquantum-well (MQW) active region that is sandwiched between two AlGaAs/GaAs distributed Bragg reflectors. Continuous wave (CW) lasing at ambient temp...

This paper presents a set of optimizations in learning algorithms commonly used for training radial basis function neural networks. These optimizations are applied to a RBF neural network used in identifying helicopter types processing their rotor sounds. The first method uses an optimum learning rate in each iteration of train process. This method increases the speed of learning process and al...