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  • Open Access

    ARTICLE

    Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

    El-Sayed M. El-kenawy1, Abdelaziz A. Abdelhamid2,3, Fadwa Alrowais4,*, Mostafa Abotaleb5, Abdelhameed Ibrahim6, Doaa Sami Khafaga4

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2885-2899, 2023, DOI:10.32604/csse.2023.034206

    Abstract Rainfall plays a significant role in managing the water level in the reservoir. The unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the reservoir. Many individuals, especially those in the agricultural sector, rely on rain forecasts. Forecasting rainfall is challenging because of the changing nature of the weather. The area of Jimma in southwest Oromia, Ethiopia is the subject of this research, which aims to develop a rainfall forecasting model. To estimate Jimma’s daily rainfall, we propose a novel approach based on optimizing the parameters of long short-term memory (LSTM) using Al-Biruni… More >

  • Open Access

    ARTICLE

    Trusted Cluster-Based Communication for Wireless Sensor Network Using Meta-Heuristic Algorithms

    Pankaj Kumar Sharma1,*, Uma Shankar Modani2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1935-1951, 2023, DOI:10.32604/csse.2023.031509

    Abstract The mobile transient and sensor network’s routing algorithm detects available multi-hop paths between source and destination nodes. However, some methods are not as reliable or trustworthy as expected. Therefore, finding a reliable method is an important factor in improving communication security. For further enhancement of protected communication, we suggest a trust cluster based secure routing (TCSR) framework for wireless sensor network (WSN) using optimization algorithms. First, we introduce an efficient cluster formation using a modified tug of war optimization (MTWO) algorithm, which provides load-balanced clusters for energy-efficient data transmission. Second, we illustrate the optimal head selection using multiple design constraints… More >

  • Open Access

    ARTICLE

    An Intelligent Hybrid Ensemble Gene Selection Model for Autism Using DNN

    G. Anurekha*, P. Geetha

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3049-3064, 2023, DOI:10.32604/iasc.2023.029127

    Abstract Autism Spectrum Disorder (ASD) is a complicated neurodevelopmental disorder that is often identified in toddlers. The microarray data is used as a diagnostic tool to identify the genetics of the disorder. However, microarray data is large and has a high volume. Consequently, it suffers from the problem of dimensionality. In microarray data, the sample size and variance of the gene expression will lead to overfitting and misclassification. Identifying the autism gene (feature) subset from microarray data is an important and challenging research area. It has to be efficiently addressed to improve gene feature selection and classification. To overcome the challenges,… More >

  • Open Access

    ARTICLE

    Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT

    Ceren Baştemur Kaya1, Ebubekir Kaya2,*, Göksel Gökkuş3

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 69-84, 2023, DOI:10.32604/csse.2023.030598

    Abstract It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since soft computing approaches are more effective than traditional approaches, studies on MPPT have shifted in this direction. This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT. The meta-heuristic training algorithms used are particle swarm optimization (PSO), harmony search (HS), cuckoo search (CS), artificial bee colony (ABC) algorithm, bee algorithm (BA), differential evolution (DE) and flower pollination algorithm (FPA). The antecedent and conclusion parameters of… More >

  • Open Access

    ARTICLE

    Availability Capacity Evaluation and Reliability Assessment of Integrated Systems Using Metaheuristic Algorithm

    A. Durgadevi*, N. Shanmugavadivoo

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1951-1971, 2023, DOI:10.32604/csse.2023.026810

    Abstract

    Contemporarily, the development of distributed generations (DGs) technologies is fetching more, and their deployment in power systems is becoming broad and diverse. Consequently, several glitches are found in the recent studies due to the inappropriate/inadequate penetrations. This work aims to improve the reliable operation of the power system employing reliability indices using a metaheuristic-based algorithm before and after DGs penetration with feeder system. The assessment procedure is carried out using MATLAB software and Modified Salp Swarm Algorithm (MSSA) that helps assess the Reliability indices of the proposed integrated IEEE RTS79 system for seven different configurations. This algorithm modifies two control… More >

  • Open Access

    ARTICLE

    Meta-heuristics for Feature Selection and Classification in Diagnostic Breast Cancer

    Doaa Sami Khafaga1, Amel Ali Alhussan1,*, El-Sayed M. El-kenawy2,3, Ali E. Takieldeen3, Tarek M. Hassan4, Ehab A. Hegazy5, Elsayed Abdel Fattah Eid6, Abdelhameed Ibrahim7, Abdelaziz A. Abdelhamid8,9

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 749-765, 2022, DOI:10.32604/cmc.2022.029605

    Abstract One of the most common kinds of cancer is breast cancer. The early detection of it may help lower its overall rates of mortality. In this paper, we robustly propose a novel approach for detecting and classifying breast cancer regions in thermal images. The proposed approach starts with data preprocessing the input images and segmenting the significant regions of interest. In addition, to properly train the machine learning models, data augmentation is applied to increase the number of segmented regions using various scaling ratios. On the other hand, to extract the relevant features from the breast cancer cases, a set… More >

  • Open Access

    ARTICLE

    Provisioning Intelligent Water Wave Optimization Approach for Underwater Acoustic Wireless Sensor Networks

    M. Manikandan1,*, A. Rajiv Kannan

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 625-641, 2022, DOI:10.32604/csse.2022.022662

    Abstract In the Acoustics channel, it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay. Subsequently, conventional re-transmission over any failure generally initiates significantly larger end-to-end delay, and therefore it is not probable for time-based services. Moreover, standard techniques without any re-transmission consume enormous energy. This investigation proposes a novel multi-hop energy-aware transmission-based intelligent water wave optimization strategy. It ensures reduced end-to-end while attaining potential amongst overall energy efficiency end-to-end packet delay. It merges a naturally inspired meta-heuristic approach with multi-hop routing for data packets to reach the… More >

  • Open Access

    ARTICLE

    Design of Energy Efficient WSN Using a Noble SMOWA Algorithm

    Avishek Banerjee1, Deepak Garg1, Victor Das2, Laxminarayan Sahoo3, Ira Nath4, Vijayakumar Varadarajan5, Ketan Kotecha6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3585-3600, 2022, DOI:10.32604/cmc.2022.025233

    Abstract In this paper, the establishment of efficient Wireless Sensor Network (WSN) networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach (SMOWA) algorithm for solving a multi-objective problem. The Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficient Wireless Sensor Network to minimize energy consumption. After that, the cluster head for each cluster has been selected with the help of the duty cycle. After configuring the WSN networks, the SMOWA algorithms have been developed to obtain the minimum energy consumption for the networks. Energy minimization,… More >

  • Open Access

    ARTICLE

    Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic Engineering

    S. Navaneetha Krishnan1, P. Sundara Vadivel2,*, D. Yuvaraj3, T. Satyanarayana Murthy4, Sree Jagadeesh Malla5, S. Nachiyappan6, S. Shanmuga Priya7

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 17-26, 2022, DOI:10.32604/csse.2022.021590

    Abstract Wireless Sensor Networks (WSN) are commonly used to observe and monitor precise environments. WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments. The base station received the amount of data collected by the numerous sensors. The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale. The Trust-Based Adaptive Acknowledgement (TRAACK) Intrusion-Detection System for Wireless Sensor Networks (WSN) is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization (MPSO) has… 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 member randomly marked by the… More >

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