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  • Open Access

    ARTICLE

    Research on Wind-Solar Complementarity Rate Analysis and Capacity Configuration Based on COPULA-IMOPSO

    Caifeng Wen1, Feifei Xue1,*, Hongliang Hao2, Edwin E. Nyakilla2, Ning Yang1,*, Yongsheng Wang3, Yuwen Zhang2

    Energy Engineering, Vol.122, No.4, pp. 1511-1529, 2025, DOI:10.32604/ee.2025.060810 - 31 March 2025

    Abstract This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output. It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity. To enable more accurate predictions of the optimal wind-solar ratio, a comprehensive complementarity rate is proposed, which allows for the optimization of wind-solar capacity based on this measure. Initially, the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power, enabling the calculation of the comprehensive complementarity rate. Following this, a joint planning… More >

  • Open Access

    ARTICLE

    An Explainable Autoencoder-Based Feature Extraction Combined with CNN-LSTM-PSO Model for Improved Predictive Maintenance

    Ishaani Priyadarshini*

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 635-659, 2025, DOI:10.32604/cmc.2025.061062 - 26 March 2025

    Abstract Predictive maintenance plays a crucial role in preventing equipment failures and minimizing operational downtime in modern industries. However, traditional predictive maintenance methods often face challenges in adapting to diverse industrial environments and ensuring the transparency and fairness of their predictions. This paper presents a novel predictive maintenance framework that integrates deep learning and optimization techniques while addressing key ethical considerations, such as transparency, fairness, and explainability, in artificial intelligence driven decision-making. The framework employs an Autoencoder for feature reduction, a Convolutional Neural Network for pattern recognition, and a Long Short-Term Memory network for temporal analysis.… More >

  • Open Access

    ARTICLE

    Employing a Diversity Control Approach to Optimize Self-Organizing Particle Swarm Optimization Algorithms

    Sung-Jung Hsiao1, Wen-Tsai Sung2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3891-3905, 2025, DOI:10.32604/cmc.2025.060056 - 06 March 2025

    Abstract For optimization algorithms, the most important consideration is their global optimization performance. Our research is conducted with the hope that the algorithm can robustly find the optimal solution to the target problem at a lower computational cost or faster speed. For stochastic optimization algorithms based on population search methods, the search speed and solution quality are always contradictory. Suppose that the random range of the group search is larger; in that case, the probability of the algorithm converging to the global optimal solution is also greater, but the search speed will inevitably slow. The smaller… More >

  • Open Access

    ARTICLE

    Prioritizing Network-On-Chip Routers for Countermeasure Techniques against Flooding Denial-of-Service Attacks: A Fuzzy Multi-Criteria Decision-Making Approach

    Ahmed Abbas Jasim Al-Hchaimi1, Yousif Raad Muhsen2,3,*, Wisam Hazim Gwad4, Entisar Soliman Alkayal5, Riyadh Rahef Nuiaa Al Ogaili6, Zaid Abdi Alkareem Alyasseri7,8, Alhamzah Alnoor9

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2661-2689, 2025, DOI:10.32604/cmes.2025.061318 - 03 March 2025

    Abstract The implementation of Countermeasure Techniques (CTs) in the context of Network-On-Chip (NoC) based Multiprocessor System-On-Chip (MPSoC) routers against the Flooding Denial-of-Service Attack (F-DoSA) falls under Multi-Criteria Decision-Making (MCDM) due to the three main concerns, called: traffic variations, multiple evaluation criteria-based traffic features, and prioritization NoC routers as an alternative. In this study, we propose a comprehensive evaluation of various NoC traffic features to identify the most efficient routers under the F-DoSA scenarios. Consequently, an MCDM approach is essential to address these emerging challenges. While the recent MCDM approach has some issues, such as uncertainty, this… More >

  • Open Access

    REVIEW

    Particle Swarm Optimization: Advances, Applications, and Experimental Insights

    Laith Abualigah*

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1539-1592, 2025, DOI:10.32604/cmc.2025.060765 - 17 February 2025

    Abstract Particle Swarm Optimization (PSO) has been utilized as a useful tool for solving intricate optimization problems for various applications in different fields. This paper attempts to carry out an update on PSO and gives a review of its recent developments and applications, but also provides arguments for its efficacy in resolving optimization problems in comparison with other algorithms. Covering six strategic areas, which include Data Mining, Machine Learning, Engineering Design, Energy Systems, Healthcare, and Robotics, the study demonstrates the versatility and effectiveness of the PSO. Experimental results are, however, used to show the strong and More >

  • Open Access

    CORRECTION

    Correction: Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space

    Mudassir Khalil1, Muhammad Imran Sharif2,*, Ahmed Naeem3, Muhammad Umar Chaudhry1, Hafiz Tayyab Rauf4,*, Adham E. Ragab5

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1461-1461, 2025, DOI:10.32604/cmc.2024.061589 - 03 January 2025

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

    Adel Binbusayyis*, Mohemmed Sha

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 909-931, 2025, DOI:10.32604/cmes.2024.058202 - 17 December 2024

    Abstract Prediction of stability in SG (Smart Grid) is essential in maintaining consistency and reliability of power supply in grid infrastructure. Analyzing the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the grid. It also possesses a better impact on averting overloading and permitting effective energy storage. Even though many traditional techniques have predicted the consumption rate for preserving stability, enhancement is required in prediction measures with minimized loss. To overcome the complications in existing studies, this paper intends to predict stability from the smart grid… More >

  • Open Access

    ARTICLE

    A Deep Learning-Based Automated Approach of Schizophrenia Detection from Facial Micro-Expressions

    Anum Saher1, Ghulam Gilanie1,*, Sana Cheema1, Akkasha Latif1, Syeda Naila Batool1, Hafeez Ullah2

    Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1053-1071, 2024, DOI:10.32604/iasc.2024.057047 - 30 December 2024

    Abstract Schizophrenia is a severe mental illness responsible for many of the world’s disabilities. It significantly impacts human society; thus, rapid, and efficient identification is required. This research aims to diagnose schizophrenia directly from a high-resolution camera, which can capture the subtle micro facial expressions that are difficult to spot with the help of the naked eye. In a clinical study by a team of experts at Bahawal Victoria Hospital (BVH), Bahawalpur, Pakistan, there were 300 people with schizophrenia and 299 healthy subjects. Videos of these participants have been captured and converted into their frames using… More >

  • Open Access

    ARTICLE

    Special Vehicle Target Detection and Tracking Based on Virtual Simulation Environment and YOLOv5-Block+DeepSort Algorithm

    Mingyuan Zhai1,2, Hanquan Zhang1, Le Wang1, Dong Xiao1,*, Zhengmin Gu3, Zhenni Li1

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3241-3260, 2024, DOI:10.32604/cmc.2024.056241 - 18 November 2024

    Abstract In the process of dense vehicles traveling fast, there will be mutual occlusion between vehicles, which will lead to the problem of deterioration of the tracking effect of different vehicles, so this paper proposes a research method of virtual simulation video vehicle target tracking based on you only look once (YOLO)v5s and deep simple online and realtime tracking (DeepSort). Given that the DeepSort algorithm is currently the most effective tracking method, this paper merges the YOLOv5 algorithm with the DeepSort algorithm. Then it adds the efficient channel attention networks (ECA-Net) focusing mechanism at the back… More >

  • Open Access

    ARTICLE

    A Comprehensive Image Processing Framework for Early Diagnosis of Diabetic Retinopathy

    Kusum Yadav1, Yasser Alharbi1, Eissa Jaber Alreshidi1, Abdulrahman Alreshidi1, Anuj Kumar Jain2, Anurag Jain3, Kamal Kumar4, Sachin Sharma5, Brij B. Gupta6,7,8,*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2665-2683, 2024, DOI:10.32604/cmc.2024.053565 - 18 November 2024

    Abstract In today’s world, image processing techniques play a crucial role in the prognosis and diagnosis of various diseases due to the development of several precise and accurate methods for medical images. Automated analysis of medical images is essential for doctors, as manual investigation often leads to inter-observer variability. This research aims to enhance healthcare by enabling the early detection of diabetic retinopathy through an efficient image processing framework. The proposed hybridized method combines Modified Inertia Weight Particle Swarm Optimization (MIWPSO) and Fuzzy C-Means clustering (FCM) algorithms. Traditional FCM does not incorporate spatial neighborhood features, making More >

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