The Cascaded Short-Term Hydrothermal Scheduling (CSTHTS) problem is a highly non-linear, multi-modal, non-convex, and NP-hard optimization that has been solved by conventional metaheuristic algorithms in the past. As CSTHTS falls under category of applied operational research, therefore, work still on-going to find new variants existing would better approximate optimal global solution shorter c...

Pattern synthesis is one of the most important aspects in antenna design. Arrays are more flexible to produce desired radiation characteristics. Difference patterns are usually generated with conventional techniques and there is less control on side lobes. In view of this, optimization techniques are applied to synthesize and produce such patterns optimally. The simulated patterns are produced ...

Plug-in hybrid electric vehicles (PHEVs) and plug-in (PEVs) have gained enormous attention for their ability to reduce fuel consumption in transportation are, thus, helpful the reduction of greenhouse effect pollution. However, they bring up some technical problems that should be resolved. Due ever-increasing demand these PHEVs, simultaneous connection large PEVs PHEVs grid can cause overloadin...

Data clustering is a recognized data analysis method in data mining whereas K-Means is the well known partitional clustering method, possessing pleasant features. We observed that, K-Means and other partitional clustering techniques suffer from several limitations such as initial cluster centre selection, preknowledge of number of clusters, dead unit problem, multiple cluster membership and pre...

CNN is particularly effective in extracting spatial features. However, the single-layer classifier constructed by activation function easily interfered image noise, resulting reduced classification accuracy. To solve problem, advanced ensemble model XGBoost used to overcome deficiency of a single classify further distinguish extracted features, CNN-XGBoost optimized APSO proposed, where optimiz...

This paper proposes an adaptive particle swarm optimization (APSO) approach to solve the grasp planning problem. Each particle represents a configuration set describing the posture of the robotic hand. The aim of this algorithm is to search for the optimum configuration that satisfies a good stability. The approach uses a Guided Random Generation (GRG) to guide the particles in the generating p...