Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (211)
  • Open Access

    ARTICLE

    Hybrid Optimization Algorithm for Handwritten Document Enhancement

    Shu-Chuan Chu1, Xiaomeng Yang1, Li Zhang2, Václav Snášel3, Jeng-Shyang Pan1,4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3763-3786, 2024, DOI:10.32604/cmc.2024.048594

    Abstract The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance; however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of… More >

  • Open Access

    ARTICLE

    MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

    Rashmi Sharma1, Ashok Pal1, Nitin Mittal2, Lalit Kumar2, Sreypov Van3, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3489-3510, 2024, DOI:10.32604/cmc.2024.046606

    Abstract This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm (MOALO) which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm (ALO) and the Genetic Algorithm (GA). MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions. The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO. A first-time hybrid of these algorithms is employed to solve… More >

  • Open Access

    ARTICLE

    Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

    Yifan Huang1, Zikang Zhou1,2, Mingyu Li1, Xuedong Luo1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3147-3165, 2024, DOI:10.32604/cmes.2024.045947

    Abstract Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management. In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR). Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed. Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter. As predictive performance evaluation indicators, the coefficient of determination (R2), root mean square… More >

  • Open Access

    ARTICLE

    Synergistic Swarm Optimization Algorithm

    Sharaf Alzoubi1, Laith Abualigah2,3,4,5,6,7,8,*, Mohamed Sharaf9, Mohammad Sh. Daoud10, Nima Khodadadi11, Heming Jia12

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2557-2604, 2024, DOI:10.32604/cmes.2023.045170

    Abstract This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm (SSOA). The SSOA combines the principles of swarm intelligence and synergistic cooperation to search for optimal solutions efficiently. A synergistic cooperation mechanism is employed, where particles exchange information and learn from each other to improve their search behaviors. This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities. Furthermore, adaptive mechanisms, such as dynamic parameter adjustment and diversification strategies, are incorporated to balance exploration and exploitation. By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation, the SSOA… More >

  • Open Access

    CORRECTION

    Correction: Learning-Based Metaheuristic Approach for Home Healthcare Optimization Problem

    Mariem Belhor1,2,3, Adnen El-Amraoui1,*, Abderrazak Jemai2, François Delmotte1

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 271-271, 2024, DOI:10.32604/csse.2023.048573

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

    Elif Varol Altay, Osman Altay, Yusuf Özçevik*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 1039-1094, 2024, DOI:10.32604/cmes.2023.029404

    Abstract Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale… More >

  • Open Access

    ARTICLE

    SCChOA: Hybrid Sine-Cosine Chimp Optimization Algorithm for Feature Selection

    Shanshan Wang1,2,3, Quan Yuan1, Weiwei Tan1, Tengfei Yang1, Liang Zeng1,2,3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3057-3075, 2023, DOI:10.32604/cmc.2023.044807

    Abstract Feature Selection (FS) is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy. However, due to the high dimensionality and complexity of the dataset, most optimization algorithms for feature selection suffer from a balance issue during the search process. Therefore, the present paper proposes a hybrid Sine-Cosine Chimp Optimization Algorithm (SCChOA) to address the feature selection problem. In this approach, firstly, a multi-cycle iterative strategy is designed to better combine the Sine-Cosine Algorithm (SCA) and the Chimp Optimization Algorithm (ChOA), enabling a more effective search in the objective space. Secondly,… More >

  • Open Access

    ARTICLE

    Using Metaheuristic OFA Algorithm for Service Placement in Fog Computing

    Riza Altunay1,2,*, Omer Faruk Bay3

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2881-2897, 2023, DOI:10.32604/cmc.2023.042340

    Abstract The use of fog computing in the Internet of Things (IoT) has emerged as a crucial solution, bringing cloud services closer to end users to process large amounts of data generated within the system. Despite its advantages, the increasing task demands from IoT objects often overload fog devices with limited resources, resulting in system delays, high network usage, and increased energy consumption. One of the major challenges in fog computing for IoT applications is the efficient deployment of services between fog clouds. To address this challenge, we propose a novel Optimal Foraging Algorithm (OFA) for task placement on appropriate fog… More >

  • Open Access

    ARTICLE

    An Enhanced Equilibrium Optimizer for Solving Optimization Tasks

    Yuting Liu1, Hongwei Ding1,*, Zongshan Wang1,*, Gaurav Dhiman2,3,4, 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 >

  • Open Access

    ARTICLE

    Computational Intelligence Driven Secure Unmanned Aerial Vehicle Image Classification in Smart City Environment

    Firas Abedi1, Hayder M. A. Ghanimi2, Abeer D. Algarni3, Naglaa F. Soliman3,*, Walid El-Shafai4,5, Ali Hashim Abbas6, Zahraa H. Kareem7, Hussein Muhi Hariz8, Ahmed Alkhayyat9

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3127-3144, 2023, DOI:10.32604/csse.2023.038959

    Abstract Computational intelligence (CI) is a group of nature-simulated computational models and processes for addressing difficult real-life problems. The CI is useful in the UAV domain as it produces efficient, precise, and rapid solutions. Besides, unmanned aerial vehicles (UAV) developed a hot research topic in the smart city environment. Despite the benefits of UAVs, security remains a major challenging issue. In addition, deep learning (DL) enabled image classification is useful for several applications such as land cover classification, smart buildings, etc. This paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification (MDLS-UAVIC) model in a smart city environment.… More >

Displaying 1-10 on page 1 of 211. Per Page