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  • Open Access


    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 plant leaf images into classes.… More >

  • Open Access


    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 to fit the sensors. Many… More >

  • Open Access


    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 introduction of the populace, semi-arbitrary… More >

  • Open Access


    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, ensemble learning, and long short-term… More >

  • Open Access


    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 winning coalition, while the… More >

  • Open Access


    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 successfully highlights the use of… More >

  • Open Access


    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 population initialization by incorporating the… More >

  • Open Access


    Hybrid Swarm Intelligence Based QoS Aware Clustering with Routing Protocol for WSN

    M. S. Maharajan1, T. Abirami2, Irina V. Pustokhina3, Denis A. Pustokhin4, K. Shankar5,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2995-3013, 2021, DOI:10.32604/cmc.2021.016139

    Abstract Wireless Sensor Networks (WSN) started gaining attention due to its wide application in the fields of data collection and information processing. The recent advancements in multimedia sensors demand the Quality of Service (QoS) be maintained up to certain standards. The restrictions and requirements in QoS management completely depend upon the nature of target application. Some of the major QoS parameters in WSN are energy efficiency, network lifetime, delay and throughput. In this scenario, clustering and routing are considered as the most effective techniques to meet the demands of QoS. Since they are treated as NP (Non-deterministic Polynomial-time) hard problem, Swarm… More >

  • Open Access


    A Novel Fault Tolerance Energy-Aware Clustering Method via Social Spider Optimization (SSO) and Fuzzy Logic and Mobile Sink in Wireless Sensor Networks (WSNs)

    Shayesteh Tabatabaei1,∗

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 477-494, 2020, DOI:10.32604/csse.2020.35.477

    Abstract In recent years, the application of WSNs has been remarkably increased and notable developments and advances have been achieved in this regard. In particular, thanks to smart, cheaper and smaller nodes, different types of information can be detected and gathered in different environments and under different conditions. As the popularity of WSNs has increased, the problems and issues related to networks are examined and investigated. As a case in point, routing issue is one of the main challenges in this regard which has a direct impact on the performance of sensor networks. In WSN routing, sensor nodes send and receive… More >

  • Open Access


    Improvement of the Firework Algorithm for Classification Problems

    Yu Xue, Sow Alpha Amadou*, Yan Zhao

    Journal of Cyber Security, Vol.2, No.4, pp. 191-196, 2020, DOI:10.32604/jcs.2020.014045

    Abstract Attracted numerous analysts’ consideration, classification is one of the primary issues in Machine learning. Numerous evolutionary algorithms (EAs) were utilized to improve their global search ability. In the previous years, many scientists have attempted to tackle this issue, yet regardless of the endeavors, there are still a few inadequacies. Based on solving the classification problem, this paper introduces a new optimization classification model, which can be applied to the majority of evolutionary computing (EC) techniques. Firework algorithm (FWA) is one of the EC methods, Although the Firework algorithm (FWA) is a proficient algorithm for solving complex optimization issue. The proficient… More >

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