Huihui Yang¹, Saif Ur Rehman Khan^2,*, Omair Bilal², Chao Chen^1,*, Ming Zhao²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2401-2434, 2025, DOI:10.32604/cmes.2025.072148 - 26 November 2025

Abstract Detecting Alzheimer’s disease is essential for patient care, as an accurate diagnosis influences treatment options. Classifying dementia from non-dementia in brain MRIs is challenging due to features such as hippocampal atrophy, while manual diagnosis is susceptible to error. Optimal computer-aided diagnosis (CAD) systems are essential for improving accuracy and reducing misclassification risks. This study proposes an optimized ensemble method (CEOE-Net) that initiates with the selection of pre-trained models, including DenseNet121, ResNet50V2, and ResNet152V2 for unique feature extraction. Each selected model is enhanced with the inclusion of a channel attention (CA) block to improve the feature… More >

He Huang, Jin Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1717-1748, 2025, DOI:10.32604/cmes.2025.068384 - 31 August 2025

Abstract Automated guided vehicles (AGVs) are key equipment in automated container terminals (ACTs), and their operational efficiency can be impacted by conflicts and battery swapping. Additionally, AGVs have bidirectional transportation capabilities, allowing them to move in the opposite direction without turning around, which helps reduce transportation time. This paper aims at the problem of AGV scheduling and bidirectional conflict-free routing with battery swapping in automated terminals. A bi-level mixed integer programming (MIP) model is proposed, taking into account task assignment, bidirectional conflict-free routing, and battery swapping. The upper model focuses on container task assignment and AGV… More >

Bin Jiang¹, Houbin Wang^2,*

Energy Engineering, Vol.122, No.5, pp. 2001-2057, 2025, DOI:10.32604/ee.2025.062765 - 25 April 2025

Abstract Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality, strong coupling, nonlinearity, and non-convexity, a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper. The algorithm is based on external elite archive and Pareto dominance, and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm. Average entropy and cubic chaotic mapping initialization strategies are proposed to increase population diversity. In the proposed method, we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.… More >

Jeng-Shyang Pan^1,2,3, Mengfei Zhang¹, Shu-Chuan Chu^2,*, Xingsi Xue⁴, Václav Snášel⁵

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 475-496, 2025, DOI:10.32604/cmc.2025.060170 - 26 March 2025

Abstract Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis. Traditional clustering algorithms, such as K-means, are widely used due to their simplicity and efficiency. This paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm (SPPE) to improve clustering performance. The SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution (PPE) algorithm. Firstly, a Variable Neighborhood Search (VNS) factor is incorporated to strengthen the local search capability and foster population diversity. Secondly, a position update model, incorporating a spiral mechanism, is… More >

Yifan Zhang¹, Qiancheng Yu^1,2,*, Lisi Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 661-677, 2024, DOI:10.32604/cmes.2023.044255 - 30 December 2023

Abstract Widely used deep neural networks currently face limitations in achieving optimal performance for purchase intention prediction due to constraints on data volume and hyperparameter selection. To address this issue, based on the deep forest algorithm and further integrating evolutionary ensemble learning methods, this paper proposes a novel Deep Adaptive Evolutionary Ensemble (DAEE) model. This model introduces model diversity into the cascade layer, allowing it to adaptively adjust its structure to accommodate complex and evolving purchasing behavior patterns. Moreover, this paper optimizes the methods of obtaining feature vectors, enhancement vectors, and prediction results within the deep More >

Yue Zhu, Tao Zhao^*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1139-1158, 2024, DOI:10.32604/cmes.2023.030178 - 17 November 2023

Abstract The optimization of the rule base of a fuzzy logic system (FLS) based on evolutionary algorithm has achieved notable results. However, due to the diversity of the deep structure in the hierarchical fuzzy system (HFS) and the correlation of each sub fuzzy system, the uncertainty of the HFS's deep structure increases. For the HFS, a large number of studies mainly use fixed structures, which cannot be selected automatically. To solve this problem, this paper proposes a novel approach for constructing the incremental HFS. During system design, the deep structure and the rule base of the… More >

Shehab Abdulhabib Alzaeemi¹, Kim Gaik Tay^1,*, Audrey Huong¹, Saratha Sathasivam², Majid Khan bin Majahar Ali²

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1163-1184, 2023, DOI:10.32604/csse.2023.038912 - 26 May 2023

Abstract Radial Basis Function Neural Network (RBFNN) ensembles have long suffered from non-efficient training, where incorrect parameter settings can be computationally disastrous. This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. Inspired by evolutionary algorithms, which can iteratively find the near-optimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN-2SAT). The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different… More >

Doaa Sami Khafaga¹, El-Sayed M. El-kenawy^2,3, Faten Khalid Karim^1,*, Sameer Alshetewi⁴, Abdelhameed Ibrahim⁵, Abdelaziz A. Abdelhamid^6,7, D. L. Elsheweikh⁸

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2379-2395, 2023, DOI:10.32604/cmc.2023.032886 - 31 October 2022

Abstract Electrocardiogram (ECG) signal is a measure of the heart’s electrical activity. Recently, ECG detection and classification have benefited from the use of computer-aided systems by cardiologists. The goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization (DTO) and Differential Evolution Algorithm (DEA) into a unified algorithm to optimize the hyperparameters of neural network (NN) for boosting the ECG classification accuracy. In addition, we proposed a new feature selection method for selecting the significant feature that can improve the overall performance. To prove the superiority of the More >

Mohamed A. Meselhi^*, Saber M. Elsayed, Daryl L. Essam, Ruhul A. Sarker

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1-17, 2023, DOI:10.32604/cmc.2023.027448 - 22 September 2022

Abstract Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time. In such problems, it is commonly assumed that all problem instances are feasible. In reality some instances can be infeasible due to various practical issues, such as a sudden change in resource requirements or a big change in the availability of resources. Decision-makers have to determine whether a particular instance is feasible or not, as infeasible instances cannot be solved as there are no solutions to implement. In this case, locating the nearest feasible solution would be… More >

Mehrdad Ahmadi Kamarposhti^1,*, Hassan Shokouhandeh², Ilhami Colak³, Kei Eguchi⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4139-4156, 2022, DOI:10.32604/cmc.2022.029011 - 16 June 2022

Abstract One method for eliminating oscillations in power systems is using stabilizers. By applying an appropriate control signal in the excitation system of a generator, a power system stabilizer improves the dynamic stability of power systems. However, the issue that is of high importance is the correct design of these stabilizers. These stabilizers must be designed to have proper performance when operating conditions change. When designed incorrectly, not only they do not improve the stability margin, but also increase the oscillations. In this paper, the robust design of power system stabilizers on a four-machine power system More >