Liya Yue¹, Pei Hu², Shu-Chuan Chu³, Jeng-Shyang Pan^3,4,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1957-1975, 2024, DOI:10.32604/cmc.2024.046962

Abstract Speech emotion recognition (SER) uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions. The number of features acquired with acoustic analysis is extremely high, so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition system. The proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum accuracy. First, we use the information gain and Fisher Score to sort the features extracted from signals. Then, we employ a multi-objective ranking method to evaluate these features and… More >

Yuting Liu¹, Hongwei Ding^1,*, Zongshan Wang^1,*, Gaurav Dhiman^2,3,4, Zhijun Yang¹, Peng Hu⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2385-2406, 2023, DOI:10.32604/cmc.2023.039883

Abstract The equilibrium optimizer (EO) represents a new, physics-inspired metaheuristic optimization approach that draws inspiration from the principles governing the control of volume-based mixing to achieve dynamic mass equilibrium. Despite its innovative foundation, the EO exhibits certain limitations, including imbalances between exploration and exploitation, the tendency to local optima, and the susceptibility to loss of population diversity. To alleviate these drawbacks, this paper introduces an improved EO that adopts three strategies: adaptive inertia weight, Cauchy mutation, and adaptive sine cosine mechanism, called SCEO. Firstly, a new update formula is conceived by incorporating an adaptive inertia weight to reach an appropriate balance… More >

Binwen Zhu¹, Qifang Luo^1,3,*, Yongquan Zhou^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 385-413, 2023, DOI:10.32604/cmes.2023.026097

Abstract With the rapid development of communication technology, the problem of antenna array optimization plays a crucial role. Among many types of antennas, line antenna arrays (LAA) are the most commonly applied, but the side lobe level (SLL) reduction is still a challenging problem. In the radiation process of the linear antenna array, the high side lobe level will interfere with the intensity of the antenna target radiation direction. Many conventional methods are ineffective in obtaining the maximum side lobe level in synthesis, and this paper proposed a quantum equilibrium optimizer (QEO) algorithm for line antenna arrays. Firstly, the linear antenna… More >

Abidhan Bardhan¹, Priyadip Manna¹, Vinay Kumar¹, Avijit Burman¹, Bojan Žlender², Pijush Samui^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1033-1067, 2021, DOI:10.32604/cmes.2021.015885

Abstract In many civil engineering projects, Piled Raft Foundations (PRFs) are usually preferred where the incoming load from the superstructures is very high. In geotechnical engineering practice, the settlement of soil layers is a critical issue for the serviceability of the structures. Thus, assessment of risk associated with the structures corresponding to the maximum allowable settlement of soils needs to be carried out in the design phase. In this study, reliability analysis of PRF based on settlement criteria is performed using a high-performance hybrid soft computing model. The new approach is an integration of the artificial neural network (ANN) and a… More >

M. Premkumar¹, R. Sowmya², Pradeep Jangir³, Kottakkaran Sooppy Nisar^4,*, Mujahed Aldhaifallah⁵

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2227-2242, 2021, DOI:10.32604/cmc.2021.015565

Abstract The Equilibrium Optimizer (EO), Grey Wolf Optimizer (GWO), and Whale Optimizer (WO) algorithms are being recently developed for engineering optimization problems. In this paper, the EO, GWO, and WO algorithms are applied individually for a brushless direct current (BLDC) design optimization problem. The EO algorithm is inspired by the models utilized to find the system’s dynamic state and equilibrium state. The GWO and WO algorithms are inspired by the hunting behavior of the wolf and the whale, respectively. The primary purpose of any optimization technique is to find the optimal configuration by maximizing motor efficiency and/or minimizing the total mass.… More >

Zonglin Fu¹, Pei Hu¹, Wei Li², Jeng-Shyang Pan^1,*, Shuchuan Chu¹

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 233-247, 2021, DOI:10.32604/iasc.2021.014192

Abstract The Equilibrium Optimizer (EO) algorithm is a novel meta-heuristic algorithm based on the strength of physics. To achieve better global search capability, a Parallel Equilibrium Optimizer algorithm, named PEO, is proposed in this paper. PEO is inspired by the idea of parallelism and adopts two different communication strategies between groups to improve EO. The first strategy is used to speed up the convergence rate and the second strategy promotes the algorithm to search for a better solution. These two kinds of communication strategies are used in the early and later iterations of PEO respectively. To check the optimization effect of… More >