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  • Open Access

    ARTICLE

    Feature Selection Using Grey Wolf Optimization with Random Differential Grouping

    R. S. Latha1,*, B. Saravana Balaji2, Nebojsa Bacanin3, Ivana Strumberger3, Miodrag Zivkovic3, Milos Kabiljo3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 317-332, 2022, DOI:10.32604/csse.2022.020487

    Abstract Big data are regarded as a tremendous technology for processing a huge variety of data in a short time and with a large storage capacity. The user’s access over the internet creates massive data processing over the internet. Big data require an intelligent feature selection model by addressing huge varieties of data. Traditional feature selection techniques are only applicable to simple data mining. Intelligent techniques are needed in big data processing and machine learning for an efficient classification. Major feature selection algorithms read the input features as they are. Then, the features are preprocessed and… More >

  • Open Access

    ARTICLE

    A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms

    Mahmoud Ragab1,2,3,*, Ali Altalbe1, Abdullah Saad Al-Malaise ALGhamdi4, S. Abdel-khalek5,6, Rashid A. Saeed7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 365-380, 2022, DOI:10.32604/cmc.2022.024932

    Abstract The smart city comprises various interlinked elements which communicate data and offers urban life to citizen. Unmanned Aerial Vehicles (UAV) or drones were commonly employed in different application areas like agriculture, logistics, and surveillance. For improving the drone flying safety and quality of services, a significant solution is for designing the Internet of Drones (IoD) where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones, where the drones were utilized for collecting the data, and communicate with More >

  • Open Access

    ARTICLE

    Archery Algorithm: A Novel Stochastic Optimization Algorithm for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi1, Mohammad Dehghani2, Pavel Trojovský2,*, Štěpán Hubálovský3, Victor Leiva4, Gaurav Dhiman5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 399-416, 2022, DOI:10.32604/cmc.2022.024736

    Abstract Finding a suitable solution to an optimization problem designed in science is a major challenge. Therefore, these must be addressed utilizing proper approaches. Based on a random search space, optimization algorithms can find acceptable solutions to problems. Archery Algorithm (AA) is a new stochastic approach for addressing optimization problems that is discussed in this study. The fundamental idea of developing the suggested AA is to imitate the archer's shooting behavior toward the target panel. The proposed algorithm updates the location of each member of the population in each dimension of the search space by a… More >

  • Open Access

    ARTICLE

    Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm

    Ayman Altameem1, Sandeep Kumar2, Ramesh Chandra Poonia3, Abdul Khader Jilani Saudagar4,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177

    Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes More >

  • Open Access

    ARTICLE

    Industrial Centric Node Localization and Pollution Prediction Using Hybrid Swarm Techniques

    R. Saravana Ram1,*, M. Vinoth Kumar2, N. Krishnamoorthy3, A. Baseera4, D. Mansoor Hussain5, N. Susila6

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 545-460, 2022, DOI:10.32604/csse.2022.021681

    Abstract Major fields such as military applications, medical fields, weather forecasting, and environmental applications use wireless sensor networks for major computing processes. Sensors play a vital role in emerging technologies of the 20th century. Localization of sensors in needed locations is a very serious problem. The environment is home to every living being in the world. The growth of industries after the industrial revolution increased pollution across the environment. Owing to recent uncontrolled growth and development, sensors to measure pollution levels across industries and surroundings are needed. An interesting and challenging task is choosing the place… More >

  • Open Access

    REVIEW

    Comparative Research Directions of Population Initialization Techniques using PSO Algorithm

    Sobia Pervaiz1, Waqas Haider Bangyal2, Adnan Ashraf3, Kashif Nisar4,*, Muhammad Reazul Haque5, Ag. Asri Bin Ag. Ibrahim4, BS Chowdhry6, Waqas Rasheed7, Joel J. P. C. Rodrigues8,9, Richard Etengu5, Danda B. Rawat10

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1427-1444, 2022, DOI:10.32604/iasc.2022.017304

    Abstract In existing meta-heuristic algorithms, population initialization forms a huge part towards problem optimization. These calculations can impact variety and combination to locate a productive ideal arrangement. Especially, for perceiving the significance of variety and intermingling, different specialists have attempted to improve the presentation of meta-heuristic algorithms. Particle Swarm Optimization (PSO) algorithm is a populace-based, shrewd stochastic inquiry strategy that is motivated by the inherent honey bee swarm food search mechanism. Population initialization is an indispensable factor in the PSO algorithm. To improve the variety and combination factors, rather than applying the irregular circulation for the… More >

  • Open Access

    ARTICLE

    Big Data Analytics Using Swarm-Based Long Short-Term Memory for Temperature Forecasting

    Malini M. Patil1,*, P. M. Rekha1, Arun Solanki2, Anand Nayyar3,4, Basit Qureshi5

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2347-2361, 2022, DOI:10.32604/cmc.2022.021447

    Abstract In the past few decades, climatic changes led by environmental pollution, the emittance of greenhouse gases, and the emergence of brown energy utilization have led to global warming. Global warming increases the Earth's temperature, thereby causing severe effects on human and environmental conditions and threatening the livelihoods of millions of people. Global warming issues are the increase in global temperatures that lead to heat strokes and high-temperature-related diseases during the summer, causing the untimely death of thousands of people. To forecast weather conditions, researchers have utilized machine learning algorithms, such as autoregressive integrated moving average,… More >

  • Open Access

    ARTICLE

    Extremal Coalitions for Influence Games Through Swarm Intelligence-Based Methods

    Fabián Riquelme1,*, Rodrigo Olivares1, Francisco Muñoz1, Xavier Molinero3, Maria Serna2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6305-6321, 2022, DOI:10.32604/cmc.2022.021804

    Abstract An influence game is a simple game represented over an influence graph (i.e., a labeled, weighted graph) on which the influence spread phenomenon is exerted. Influence games allow applying different properties and parameters coming from cooperative game theory to the contexts of social network analysis, decision-systems, voting systems, and collective behavior. The exact calculation of several of these properties and parameters is computationally hard, even for a small number of players. Two examples of these parameters are the length and the width of a game. The length of a game is the size of its smaller… More >

  • Open Access

    ARTICLE

    Multi-Objective High-Fidelity Optimization Using NSGA-III and MO-RPSOLC

    N. Ganesh1, Uvaraja Ragavendran2, Kanak Kalita3,*, Paras Jain4, Xiao-Zhi Gao5

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 443-464, 2021, DOI:10.32604/cmes.2021.014960

    Abstract Optimizing the performance of composite structures is a real-world application with significant benefits. In this paper, a high-fidelity finite element method (FEM) is combined with the iterative improvement capability of metaheuristic optimization algorithms to obtain optimized composite plates. The FEM module comprises of ninenode isoparametric plate bending element in conjunction with the first-order shear deformation theory (FSDT). A recently proposed memetic version of particle swarm optimization called RPSOLC is modified in the current research to carry out multi-objective Pareto optimization. The performance of the MO-RPSOLC is found to be comparable with the NSGA-III. This work More >

  • Open Access

    ARTICLE

    Particle Swarm Optimization with New Initializing Technique to Solve Global Optimization Problems

    Adnan Ashraf1, Abdulwahab Ali Almazroi2, Waqas Haider Bangyal3,*, Mohammed A. Alqarni4

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 191-206, 2022, DOI:10.32604/iasc.2022.015810

    Abstract Particle Swarm Optimization (PSO) is a well-known extensively utilized algorithm for a distinct type of optimization problem. In meta-heuristic algorithms, population initialization plays a vital role in solving the classical problems of optimization. The population’s initialization in meta-heuristic algorithms urges the convergence rate and diversity, besides this, it is remarkably beneficial for finding the efficient and effective optimal solution. In this study, we proposed an enhanced variation of the PSO algorithm by using a quasi-random sequence (QRS) for population initialization to improve the convergence rate and diversity. Furthermore, this study represents a new approach for… More >

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