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  • Open Access

    ARTICLE

    IRKO: An Improved Runge-Kutta Optimization Algorithm for Global Optimization Problems

    R. Manjula Devi1, M. Premkumar2, Pradeep Jangir3, Mohamed Abdelghany Elkotb4,5, Rajvikram Madurai Elavarasan6, Kottakkaran Sooppy Nisar7,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4803-4827, 2022, DOI:10.32604/cmc.2022.020847

    Abstract Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost, gains, energy, mass, and so on. In order to solve optimization problems, metaheuristic algorithms are essential. Most of these techniques are influenced by collective knowledge and natural foraging. There is no such thing as the best or worst algorithm; instead, there are more effective algorithms for certain problems. Therefore, in this paper, a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization (RKO) algorithm, called Improved Runge-Kutta Optimization (IRKO) algorithm, is suggested for solving optimization problems. The IRKO is formulated using the basic RKO and… More >

  • Open Access

    ARTICLE

    A Novel Binary Emperor Penguin Optimizer for Feature Selection Tasks

    Minakshi Kalra1, Vijay Kumar2, Manjit Kaur3, Sahar Ahmed Idris4, Şaban Öztürk5, Hammam Alshazly6,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6239-6255, 2022, DOI:10.32604/cmc.2022.020682

    Abstract Nowadays, due to the increase in information resources, the number of parameters and complexity of feature vectors increases. Optimization methods offer more practical solutions instead of exact solutions for the solution of this problem. The Emperor Penguin Optimizer (EPO) is one of the highest performing meta-heuristic algorithms of recent times that imposed the gathering behavior of emperor penguins. It shows the superiority of its performance over a wide range of optimization problems thanks to its equal chance to each penguin and its fast convergence features. Although traditional EPO overcomes the optimization problems in continuous search space, many problems today shift… More >

  • Open Access

    ARTICLE

    Training Multi-Layer Perceptron with Enhanced Brain Storm Optimization Metaheuristics

    Nebojsa Bacanin1, Khaled Alhazmi2,*, Miodrag Zivkovic1, K. Venkatachalam3, Timea Bezdan1, Jamel Nebhen4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4199-4215, 2022, DOI:10.32604/cmc.2022.020449

    Abstract In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing… More >

  • Open Access

    ARTICLE

    Path Planning of Quadrotors in a Dynamic Environment Using a Multicriteria Multi-Verse Optimizer

    Raja Jarray1, Mujahed Al-Dhaifallah2,*, Hegazy Rezk3,4, Soufiene Bouallègue1,5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2159-2180, 2021, DOI:10.32604/cmc.2021.018752

    Abstract Paths planning of Unmanned Aerial Vehicles (UAVs) in a dynamic environment is considered a challenging task in autonomous flight control design. In this work, an efficient method based on a Multi-Objective Multi-Verse Optimization (MOMVO) algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving obstacles. Such a path planning task is formulated as a multicriteria optimization problem under operational constraints. The proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving obstacles. The vehicle moves to the next position… More >

  • Open Access

    ARTICLE

    A survey on the Metaheuristics for Cryptanalysis of Substitution and Transposition Ciphers

    Arkan Kh Shakr Sabonchi*, Bahriye Akay

    Computer Systems Science and Engineering, Vol.39, No.1, pp. 87-106, 2021, DOI:10.32604/csse.2021.05365

    Abstract This paper presents state-of-art cryptanalysis studies on attacks of the substitution and transposition ciphers using various metaheuristic algorithms. Traditional cryptanalysis methods employ an exhaustive search, which is computationally expensive. Therefore, metaheuristics have attracted the interest of researchers in the cryptanalysis field. Metaheuristic algorithms are known for improving the search for the optimum solution and include Genetic Algorithm, Simulated Annealing, Tabu Search, Particle Swarm Optimization, Differential Evolution, Ant Colony, the Artificial Bee Colony, Cuckoo Search, and Firefly algorithms. The most important part of these various applications is deciding the fitness function to guide the search. This review presents how these algorithms… More >

  • Open Access

    ARTICLE

    Flower Pollination Heuristics for Parameter Estimation of Electromagnetic Plane Waves

    Sadiq Akbar1, Muhammad Asif Zahoor Raja2,*, Naveed Ishtiaq Chaudhary3, Fawad Zaman4, Hani Alquhayz5

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2529-2543, 2021, DOI:10.32604/cmc.2021.016097

    Abstract For the last few decades, the parameter estimation of electromagnetic plane waves i.e., far field sources, impinging on antenna array geometries has attracted a lot of researchers due to their use in radar, sonar and under water acoustic environments. In this work, nature inspired heuristics based on the flower pollination algorithm (FPA) is designed for the estimation problem of amplitude and direction of arrival of far field sources impinging on uniform linear array (ULA). Using the approximation in mean squared error sense, a fitness function of the problem is developed and the strength of the FPA is utilized for optimization… More >

  • Open Access

    ARTICLE

    Paddy Leaf Disease Detection Using an Optimized Deep Neural Network

    Shankarnarayanan Nalini1,*, Nagappan Krishnaraj2, Thangaiyan Jayasankar3, Kalimuthu Vinothkumar4, Antony Sagai Francis Britto5, Kamalraj Subramaniam6, Chokkalingam Bharatiraja7

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1117-1128, 2021, DOI:10.32604/cmc.2021.012431

    Abstract Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop. Plant diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming crops. Recognition of diseases from the plant images is an active research topic which makes use of machine learning (ML) approaches. A novel deep neural network (DNN) classification model is proposed for the identification of paddy leaf disease using plant image data. Classification errors were minimized by optimizing weights and biases in the DNN model using a crow search… More >

  • Open Access

    ARTICLE

    Control Strategy for a Quadrotor Based on a Memetic Shuffled Frog Leaping Algorithm

    Nour Ben Ammar1, Hegazy Rezk2,3,*, Soufiene Bouallègue1,4

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 4081-4100, 2021, DOI:10.32604/cmc.2021.015681

    Abstract This work presents a memetic Shuffled Frog Leaping Algorithm (SFLA) based tuning approach of an Integral Sliding Mode Controller (ISMC) for a quadrotor type of Unmanned Aerial Vehicles (UAV). Based on the Newton–Euler formalism, a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes. Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law, which are usually selected by repetitive and time-consuming trials-errors based procedures, a constrained optimization problem is formulated for the systematically tuning of these unknown variables. Under time-domain operating… More >

  • Open Access

    ARTICLE

    A Heuristics-Based Cost Model for Scientific Workflow Scheduling in Cloud

    Ehab Nabiel Al-Khanak1,*, Sai Peck Lee2, Saif Ur Rehman Khan3, Navid Behboodian4, Osamah Ibrahim Khalaf5, Alexander Verbraeck6, Hans van Lint1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3265-3282, 2021, DOI:10.32604/cmc.2021.015409

    Abstract Scientific Workflow Applications (SWFAs) can deliver collaborative tools useful to researchers in executing large and complex scientific processes. Particularly, Scientific Workflow Scheduling (SWFS) accelerates the computational procedures between the available computational resources and the dependent workflow jobs based on the researchers’ requirements. However, cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate (near-optimal) solution within polynomial computational time. Motivated by this, current work proposes a novel SWFS cost optimization model effective in solving this challenge. The proposed model contains three main stages: (i) scientific workflow application, (ii) targeted computational environment,… More >

  • Open Access

    ARTICLE

    Technology Landscape for Epidemiological Prediction and Diagnosis of COVID-19

    Siddhant Banyal1, Rinky Dwivedi2, Koyel Datta Gupta2, Deepak Kumar Sharma3,*, Fadi Al-Turjman4, Leonardo Mostarda5

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1679-1696, 2021, DOI:10.32604/cmc.2021.014387

    Abstract The COVID-19 outbreak initiated from the Chinese city of Wuhan and eventually affected almost every nation around the globe. From China, the disease started spreading to the rest of the world. After China, Italy became the next epicentre of the virus and witnessed a very high death toll. Soon nations like the USA became severely hit by SARS-CoV-2 virus. The World Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the world has instituted various policies like physical distancing, isolation of infected population and researching on the potential vaccine… More >

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