Abstract With the rapid development of modern wireless technology, it is necessary to continuously optimize microwave devices meet higher requirements communication systems. In this paper, we propose a device optimization method based on extreme learning machine (ELM) and gray wolf optimizer (GWO). adopt GWO parameters ELM establish mapping relationships between design their responses. Accordin...

Photovoltaic (PV) intelligent edge terminals (IETs) integrate data acquisition, processing, storage and upload functions for operations of PV power stations. However, the cost installing a IET at one station is relatively high. In order to achieve goal multiple distributed stations sharing on premise ensuring reliability, paper proposes method optimal configuration IETs. First all, considering ...

Abstract A combined prediction model based on long short-term memory neural network (LSTM) and convolutional (CNN) is proposed in order to increase the accuracy of load. To address issue that gray wolf optimization (GWO) search process prone falling into local optimum. An improved grey algorithm (IGWO) update convergence factor using lower incomplete gamma function improve global performance. T...

In this paper, a novel hybrid Maximum Power Point Tracking (MPPT) algorithm using Particle-Swarm-Optimization-trained machine learning and Flying Squirrel Search Optimization (PSO_ML-FSSO) has been proposed to obtain the optimal efficiency for solar PV systems. The was compared with other well-known methods viz. Perturb & Observer (P&O), Incremental Conductance (INC), Particle Swarm (PS...

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates ...

The existing original BP neural network models for wood performance prediction have low fitting accuracy and imprecise results. We propose a nonlinear, adaptive grouping gray wolf optimization (NAGGWO)-BP model prediction. Firstly, the (GWO) algorithm is optimized. CPM mapping (the Chebyshev method combined with piecewise followed by mod operation) to generate initial populations improve popula...

Automatic tooth arrangement and path planning play an essential role in computer-aided orthodontic treatment. However, state-of-the-art methods have some shortcomings: low efficiency, excessive cost of displacements or collisions insufficient accuracy. To address these issues, this paper proposes innovative method based on the improved gray wolf optimization algorithm, which is called OPP-IGWO....

Received Dec 24, 2016 Revised Apr 26, 2017 Accepted Jun 14, 2017 The augment of ecological shield and the progressive exhaustion of traditional fossil energy sources have increased the interests in integrating renewable energy sources into existing power system. Wind power is becoming worldwide a significant component of the power generation portfolio. Profuse literatures have been reported for...

In recent years, finding the optimal solution for image segmentation has become more important in many applications. The whale optimization algorithm (WOA) is a metaheuristic technique that advantage of achieving global while also being simple to implement and solving real-time problems. If complexity problem increases, WOA may stick local optima rather than optima. This could be an issue obtai...