Salp swarm algorithm (SSA) is a relatively new bio-inspired meta-heuristic optimization that mimics the navigating and foraging behavior of salps in oceans. This paper presents an orthogonal quasi-opposition-based learning-driven dynamic SSA (OBDSSA) for solving global problems. The proposed methodology integrates learning (OQOBL) tactic (DL) strategy with to improve its performance. OQOBL tech...

Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...

Designing an efficient wireless sensor network (WSN) system is considered a challenging problem due to the limited energy supply per node. In this paper, performance of several bi-objective optimization algorithms in providing energy-efficient clustering solutions that can extend lifetime nodes were investigated. Specifically, we use Moth–Flame Optimization (MFO) algorithm and Salp Swarm Algori...

The basic thought of particle swarm optimization is introduced firstly, then particle swarm optimization algorithm model is established. The application of the improved particle swarm optimization algorithm to power supply system fault diagnosis is analyzed in accordance with problem of the algorithm, and migration strategy is added to particle swarm optimization algorithm. Finally the paramete...

with the rapid development of the internet, the amount of information and data which are produced, are extremely massive. hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. data mining can overcome this problem. while data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. as the speed of ...