In Smart Grid Demand side management (DSM) plays a crucial role which permits customers to form educated selections concerning their energy consumption. It allows the strength companies lessen height load call for and reshape burden profile. Most of present demand aspect ways utilized in ancient system is with specific techniques algorithms. addition, handle solely restricted range governable l...

Abstract This paper presents an online path planning approach for autonomous tracked vehicle in a cluttered environment based on teaching–learning-based optimization (TLBO), considering the smoothness, and potential collision with surrounding obstacles. In order to plan efficient that allows be autonomously navigated environments, problem is solved as multi-objective problem. First, perception ...

Cluster analysis has received attention in many scientific fields. The purpose of clustering analysis is to detect group data points, which are close to one another. One of the most widely used techniques for clustering is the K-means algorithm. The performance of K-means algorithm which converges to numerous local minima depends highly on initial cluster centers. In order to overcome local opt...

Abstract Solving nonlinear equation systems (NESs) requires locating different roots in one run. To effectively deal with NESs, a multi-population cooperative teaching–learning-based optimization, named MCTLBO, is presented. The innovations of MCTLBO are as follows: (i) two niching technique (crowding and improved speciation) integrated into the algorithm to enhance population diversity; (ii) a...

Reactive power planning is one of the most challenging problem for efficient and source operation of an interconnected power network. It requires effective and optimum co-ordination of all the reactive power sources present in the network. Recently, Teaching Learning Based Optimization (TLBO) algorithm is evolved and finds its application in the field of engineering optimization. In the propose...

Aiming to effectively recognize train center plate bolt loss faults, this paper presents an improved fault detection method. A multi-scale local binary pattern operator containing the local texture information of different radii is designed to extract more efficient discrimination information. An improved teaching-learning-based optimization algorithm is established to optimize the classificati...