This paper studies optimization of tool path planning in 5-axis flank milling of ruled surfaces using advanced Particle Swarm Optimization (PSO) methods with machining error as an objective. We enlarge the solution space in the optimization by relaxing the constraint imposed by previous studies that the cutter must make contact with the boundary curves. Advanced Particle Swarm Optimization (APS...

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...

This paper exposes a comparative study that was made between the adaptive particle swarm optimization (APSO) and hybrid model genetical optimizer approaches (GSO) for synthesis of 1-D equally spaced annular ring antenna arrays both TM11 TM12 modes. The uniform is designed as mono objective problem. employed techniques are compared in terms convergence rate side lobes level reduction. Several or...

A control strategy for power maximization which is an important mechanism to extract maximum under changing environmental conditions using Adaptive Particle Swarm Optimization (APSO) proposed in this paper. An Inertia Weighting Factor (AIWF) utilized the velocity update equation of traditional PSO improvement speed convergence and precision tracking Maximum Power Point (MPP) standalone Photovol...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...

Heart chaotic system and the ability of particle swarm optimization (PSO) method motivated us to benefit the method of chaotic particle swarm optimization (CPSO) to synchronize the heart three-oscillator model. It can be a suitable algorithm for strengthening the controller in presence of unknown parameters. In this paper we apply adaptive control (AC) on heart delay model, also examine the sys...

The infrastructure build in the big data platform is reliable to challenge the commercial and noncommercial IT development communities of data streams in high dimensional data cluster modeling. The APSO ie., Accelerated Particle Swarm Optimization is a technique which commonly known for data's are sourced to accumulate their continuation in the batch model induction algorithms which is not feas...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

In this paper, cantilever retaining wall design is studied as an important optimization task in civil engineering. The current study explores the efficiency of some recent swarm intelligence techniques: accelerated particle swarm optimization (APSO), firefly algorithm (FA), and cuckoo search (CS). These algorithms are verified using two benchmark case studies. In order to better determine the p...

Selecting an optimal threshold value is the most important step in image thresholding algorithms. For a bimodal histogram which can be modeled as a mixture of two Gaussian density functions, estimating these densities in practice is not simply feasible. The objective of this paper is to use adaptive particle swarm optimization (APSO) for the suboptimal estimation of the means and variances of t...