Traffic accidents on urban roads are a major cause of death despite the development traffic safety measures. However, prediction casualties in road has not been deeply explored previous research. Effective forecasting methods for can improve manner accident warnings, further avoiding unnecessary loss. This paper provides practicable model forecast problems, which ten variables, including time c...

Identification of coal and gangue is one the important problems in industry. To improve accuracy identification mining process, a method based on histogram oriented gradient (HOG) combined with local binary pattern (LBP) features improved support vector machine (SVM) was proposed. First, according to actual underground working environment mine, vision platform for built image acquisition experi...

To investigate the performance potential of aero-propulsion system and problem control mode conversion, this paper takes inlet/engine integrated component-level model as research object, a performance-seeking (PSC) scheme based on neighborhood-based speciation differential evolution–grey wolf optimization (NSDE-GWO) algorithm is designed combined with an active disturbance rejection (ADRC) to e...

The Jiles-Atherton model is key to researching the hysteresis loop. focus of scholars across various countries has always been parameter identification model. This paper on Levy whale optimization algorithm (LWOA), based (WOA), proposes overcome disadvantage that WOA tends involve local optimum. recommended uses flight strategy instead encircling prey policy since former improves global search....

Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples SI algorithms have been selected and thoroughly described, namely Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Salp (SSA). Firstly, are reviewed literature, specifically for optimization problems antenna design. Secondly, a compa...

Grey wolf optimization (GWO) is a recent and popular swarm-based metaheuristic approach. It has been used in numerous fields such as numerical optimization, engineering problems, machine learning. The different variants of GWO have developed the last 5 years for solving problems diverse fields. Like other algorithms, also suffers from local optima slow convergence resulted degraded performance....

In this work, a novel binary version of the grey wolf optimization (GWO) is proposed and used to select optimal feature subset for classification purposes. Grey wolf optimizer (GWO) is one of the latest bioinspired optimization techniques, which simulate the hunting process of grey wolves in nature. The binary version introduced here is performed using two different approaches. In the first app...

Flexible AC transmission systems (FACTS) and optimal power-flow (OPF) solutions play an important role in solving power operation problems. The volatile nature of the generation profiles from renewable energy sources, solar wind systems, determining locations sizes FACTS devices increase complexity OPF problems modern network models, such as loss, cost voltage deviation, a highly nonlinear-nonc...

Electric buses have many significant advantages, such as zero emissions and low noise energy consumption, making them play an important role in saving the operation cost of bus companies reducing urban traffic pollution emissions. Therefore, recent years, cities world dedicate to promoting electrification public transport vehicles. Whereas due limitation on-board battery capacity, driving range...

In recent years, localization has become a hot issue in many applications of the Internet Things (IoT). The distance vector-hop (DV-Hop) algorithm is accepted for fields due to its uncomplicated, low-budget, and common hardware, but it disadvantage low positioning accuracy. To solve this issue, an improved DV-Hop algorithm—TWGDV-Hop—is put forward article. Firstly, position broadcast by using t...