Ting-Yu Lin¹, Kuo-Chen Hung^2,*, Josef Jablonsky³, Kuo-Ping Lin¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1901-1927, 2025, DOI:10.32604/cmc.2025.063543 - 16 April 2025

Abstract VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) has been developed and applied for over twenty-five years, gaining recognition as a prominent multi-criteria decision-making (MCDM) method. Over this period, numerous studies have explored its applications, conducted comparative analyses, integrated it with other methods, and proposed various modifications to enhance its performance. This paper aims to delve into the fundamental principles and objectives of VIKOR, which aim to maximize group utility and minimize individual regret simultaneously. However, this study identifies a significant limitation in the VIKOR methodology: its process amplifies the weight of individual regret, and the calculated… More >

Ahmed El Youssefi¹, Abdelaaziz Hessane^1,2, Imad Zeroual¹, Yousef Farhaoui^1,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3411-3433, 2025, DOI:10.32604/cmc.2025.063218 - 16 April 2025

Abstract This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators. In this work, over 130 technical indicators—covering momentum, volatility, volume, and trend-related technical indicators—are subjected to three distinct feature selection approaches. Specifically, mutual information (MI), recursive feature elimination (RFE), and random forest importance (RFI). By extracting an optimal set of 20 predictors, the proposed framework aims to mitigate redundancy and overfitting while enhancing interpretability. These feature subsets are integrated into support vector regression (SVR), Huber regressors, and k-nearest neighbors (KNN) models to forecast the… More >

Ilesanmi Afolabi Daniyan^1,*, Rumbidzai Muvunzi², Festus Fameso³, Julius Ndambuki³, Williams Kupolati³, Jacques Snyman³

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1623-1648, 2025, DOI:10.32604/cmc.2025.062092 - 16 April 2025

Abstract This study evaluates the Fuzzy Analytical Hierarchy Process (FAHP) as a multi-criteria decision (MCD) support tool for selecting appropriate additive manufacturing (AM) techniques that align with cleaner production and environmental sustainability. The FAHP model was validated using an example of the production of aircraft components (specifically fuselage) employing AM technologies such as Wire Arc Additive Manufacturing (WAAM), laser powder bed fusion (L-PBF), Binder Jetting (BJ), Selective Laser Sintering (SLS), and Laser Metal Deposition (LMD). The selection criteria prioritized eco-friendly manufacturing considerations, including the quality and properties of the final product (e.g., surface finish, high strength,… More >

Weitao Ha¹, Sheng Gang², Yahya D. Navaei³, Abubakar S. Gezawa⁴, Yaser A. Nanehkaran^2,5,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3025-3057, 2025, DOI:10.32604/cmc.2025.061343 - 16 April 2025

Abstract Music recommendation systems are essential due to the vast amount of music available on streaming platforms, which can overwhelm users trying to find new tracks that match their preferences. These systems analyze users’ emotional responses, listening habits, and personal preferences to provide personalized suggestions. A significant challenge they face is the “cold start” problem, where new users have no past interactions to guide recommendations. To improve user experience, these systems aim to effectively recommend music even to such users by considering their listening behavior and music popularity. This paper introduces a novel music recommendation system… More >

Mengjiao Wei^1,*, Wenyu Liu²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2505-2523, 2025, DOI:10.32604/cmc.2025.060887 - 16 April 2025

Abstract In recent years, decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios. In these algorithms, the reference vectors of the Penalty-Based boundary intersection (PBI) are distributed parallelly while those based on the normal boundary intersection (NBI) are distributed radially in a conical shape in the objective space. To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications, this paper addresses the improvement of the Collaborative Decomposition (CoD) method, a multi-objective decomposition technique that integrates PBI and NBI, and combines it with the Elephant Clan Optimization Algorithm, introducing the… More >

Iman S. Al-Mahdi¹, Saad M. Darwish^1,*, Magda M. Madbouly²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 875-909, 2025, DOI:10.32604/cmes.2025.061623 - 11 April 2025

Abstract Heart disease prediction is a critical issue in healthcare, where accurate early diagnosis can save lives and reduce healthcare costs. The problem is inherently complex due to the high dimensionality of medical data, irrelevant or redundant features, and the variability in risk factors such as age, lifestyle, and medical history. These challenges often lead to inefficient and less accurate models. Traditional prediction methodologies face limitations in effectively handling large feature sets and optimizing classification performance, which can result in overfitting poor generalization, and high computational cost. This work proposes a novel classification model for heart… More >

Zihang Wang¹, Ying Peng¹, Xiong Lan², Xiaoyu Bai³, Chao Deng¹, Yuan Ren^1,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 643-664, 2025, DOI:10.32604/sdhm.2025.060302 - 03 April 2025

Abstract To investigate the influence of different longitudinal constraint systems on the longitudinal displacement at the girder ends of a three-tower suspension bridge, this study takes the Cangrong Xunjiang Bridge as an engineering case for finite element analysis. This bridge employs an unprecedented tower-girder constraint method, with all vertical supports placed at the transition piers at both ends. This paper aims to study the characteristics of longitudinal displacement control at the girder ends under this novel structure, relying on finite element (FE) analysis. Initially, based on the Weigh In Motion (WIM) data, a random vehicle load… More >

Wenchang Yu¹, Xiaoqin Ma^1,2, Zheqing Zhang¹, Qinli Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1195-1218, 2025, DOI:10.32604/cmc.2025.060833 - 26 March 2025

Abstract Feature selection methods rooted in rough sets confront two notable limitations: their high computational complexity and sensitivity to noise, rendering them impractical for managing large-scale and noisy datasets. The primary issue stems from these methods’ undue reliance on all samples. To overcome these challenges, we introduce the concept of cross-similarity grounded in a robust fuzzy relation and design a rapid and robust feature selection algorithm. Firstly, we construct a robust fuzzy relation by introducing a truncation parameter. Then, based on this fuzzy relation, we propose the concept of cross-similarity, which emphasizes the sample-to-sample similarity relations… More >

Abdul Ahad^1,2, Ira Puspitasari^1,3,*, Jiangbin Zheng², Shamsher Ullah⁴, Farhan Ullah⁵, Sheikh Tahir Bakhsh⁶, Ivan Miguel Pires^7,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5115-5134, 2025, DOI:10.32604/cmc.2025.062605 - 06 March 2025

Abstract This research explores the use of Fuzzy K-Nearest Neighbor (F-KNN) and Artificial Neural Networks (ANN) for predicting heart stroke incidents, focusing on the impact of feature selection methods, specifically Chi-Square and Best First Search (BFS). The study demonstrates that BFS significantly enhances the performance of both classifiers. With BFS preprocessing, the ANN model achieved an impressive accuracy of 97.5%, precision and recall of 97.5%, and an Receiver Operating Characteristics (ROC) area of 97.9%, outperforming the Chi-Square-based ANN, which recorded an accuracy of 91.4%. Similarly, the F-KNN model with BFS achieved an accuracy of 96.3%, precision More >

Digambar Singh¹, Najat Elgeberi², Mohammad Aljaidi^3,*, Ramesh Kumar^4,5, Rabia Emhamed Al Mamlook⁶, Manish Kumar Singla^4,7,8,*

Energy Engineering, Vol.122, No.3, pp. 823-859, 2025, DOI:10.32604/ee.2025.059309 - 07 March 2025

Abstract The literature on multi-attribute optimization for renewable energy source (RES) placement in deregulated power markets is extensive and diverse in methodology. This study focuses on the most relevant publications directly addressing the research problem at hand. Similarly, while the body of work on optimal location and sizing of renewable energy generators (REGs) in balanced distribution systems is substantial, only the most pertinent sources are cited, aligning closely with the study’s objective function. A comprehensive literature review reveals several key research areas: RES integration, RES-related optimization techniques, strategic placement of wind and solar generation, and RES… More >