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  • Open Access

    ARTICLE

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

    Wenchao Yi, Zhilei Lin, Yong Chen, Zhi Pei*, Jiansha Lu

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2841-2860, 2023, DOI:10.32604/cmes.2023.027055 - 09 March 2023

    Abstract Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated ε-level method is proposed to avoid trapping in infeasible More > Graphic Abstract

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

  • Open Access

    ARTICLE

    Quantum Inspired Differential Evolution with Explainable Artificial Intelligence-Based COVID-19 Detection

    Abdullah M. Basahel, Mohammad Yamin*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 209-224, 2023, DOI:10.32604/csse.2023.034449 - 20 January 2023

    Abstract Recent advancements in the Internet of Things (Io), 5G networks, and cloud computing (CC) have led to the development of Human-centric IoT (HIoT) applications that transform human physical monitoring based on machine monitoring. The HIoT systems find use in several applications such as smart cities, healthcare, transportation, etc. Besides, the HIoT system and explainable artificial intelligence (XAI) tools can be deployed in the healthcare sector for effective decision-making. The COVID-19 pandemic has become a global health issue that necessitates automated and effective diagnostic tools to detect the disease at the initial stage. This article presents… More >

  • Open Access

    ARTICLE

    Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol

    Manar Ahmed Hamza1,*, Haya Mesfer Alshahrani2, Sami Dhahbi3, Mohamed K Nour4, Mesfer Al Duhayyim5, ElSayed M. Tag El Din6, Ishfaq Yaseen1, Abdelwahed Motwakel1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1759-1773, 2023, DOI:10.32604/csse.2023.030581 - 03 November 2022

    Abstract Wireless Sensor Networks (WSN) has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of applications. In spite of this, it is challenging to design energy-efficient WSN. The routing approaches are leveraged to reduce the utilization of energy and prolonging the lifespan of network. In order to solve the restricted energy problem, it is essential to reduce the energy utilization of data, transmitted from the routing protocol and improve network development. In this background, the current study proposes a novel Differential… More >

  • Open Access

    ARTICLE

    Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

    Doaa Sami Khafaga1, El-Sayed M. El-kenawy2,3, Faten Khalid Karim1,*, Sameer Alshetewi4, Abdelhameed Ibrahim5, Abdelaziz A. Abdelhamid6,7, D. L. Elsheweikh8

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2379-2395, 2023, DOI:10.32604/cmc.2023.032886 - 31 October 2022

    Abstract Electrocardiogram (ECG) signal is a measure of the heart’s electrical activity. Recently, ECG detection and classification have benefited from the use of computer-aided systems by cardiologists. The goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization (DTO) and Differential Evolution Algorithm (DEA) into a unified algorithm to optimize the hyperparameters of neural network (NN) for boosting the ECG classification accuracy. In addition, we proposed a new feature selection method for selecting the significant feature that can improve the overall performance. To prove the superiority of the More >

  • Open Access

    ARTICLE

    Temperature Control Design with Differential Evolution Based Improved Adaptive-Fuzzy-PID Techniques

    Prabhu Kaliappan1,*, Aravindaguru Ilangovan2, Sivachitra Muthusamy3, Banumathi Sembanan4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 781-801, 2023, DOI:10.32604/iasc.2023.030047 - 29 September 2022

    Abstract This paper presents the design and performance analysis of Differential Evolution (DE) algorithm based Proportional-Integral-Derivative (PID) controller for temperature control of Continuous Stirred Tank Reactor (CSTR) plant in chemical industries. The proposed work deals about the design of Differential Evolution (DE) algorithm in order to improve the performance of CSTR. In this, the process is controlled by controlling the temperature of the liquid through manipulation of the coolant flow rate with the help of modified Model Reference Adaptive Controller (MRAC). The transient response of temperature process is improved by using PID Controller, Differential Evolution Algorithm More >

  • Open Access

    ARTICLE

    Hybrid Global Optimization Algorithm for Feature Selection

    Ahmad Taher Azar1,2,*, Zafar Iqbal Khan2, Syed Umar Amin2, Khaled M. Fouad1,3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2021-2037, 2023, DOI:10.32604/cmc.2023.032183 - 22 September 2022

    Abstract This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has introduced the benefits of Parallel computing into the combined power of TVAC (Time-Variant Acceleration Coefficients) and IW (Inertial Weight). Proposed algorithm has been tested against linear, non-linear, traditional, and multiswarm based optimization algorithms. An experimental study is performed in two stages to assess the proposed PLTVACIW-PSO. Phase I uses 12 recognized Standard Benchmarks methods to evaluate the comparative performance of the proposed PLTVACIW-PSO vs. IW based Particle Swarm Optimization (PSO) algorithms, TVAC based PSO algorithms, traditional… More >

  • Open Access

    ARTICLE

    Modified Differential Evolution Algorithm for Solving Dynamic Optimization with Existence of Infeasible Environments

    Mohamed A. Meselhi*, Saber M. Elsayed, Daryl L. Essam, Ruhul A. Sarker

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1-17, 2023, DOI:10.32604/cmc.2023.027448 - 22 September 2022

    Abstract Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time. In such problems, it is commonly assumed that all problem instances are feasible. In reality some instances can be infeasible due to various practical issues, such as a sudden change in resource requirements or a big change in the availability of resources. Decision-makers have to determine whether a particular instance is feasible or not, as infeasible instances cannot be solved as there are no solutions to implement. In this case, locating the nearest feasible solution would be… More >

  • Open Access

    ARTICLE

    An Efficient Differential Evolution for Truss Sizing Optimization Using AdaBoost Classifier

    Tran-Hieu Nguyen*, Anh-Tuan Vu

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 429-458, 2023, DOI:10.32604/cmes.2022.020819 - 24 August 2022

    Abstract Design constraints verification is the most computationally expensive task in evolutionary structural optimization due to a large number of structural analyses that must be conducted. Building a surrogate model to approximate the behavior of structures instead of the exact structural analyses is a possible solution to tackle this problem. However, most existing surrogate models have been designed based on regression techniques. This paper proposes a novel method, called CaDE, which adopts a machine learning classification technique for enhancing the performance of the Differential Evolution (DE) optimization. The proposed method is separated into two stages. During… More >

  • Open Access

    ARTICLE

    Butterfly Optimized Feature Selection with Fuzzy C-Means Classifier for Thyroid Prediction

    S. J. K. Jagadeesh Kumar1, P. Parthasarathi2, Mehedi Masud3, Jehad F. Al-Amri4, Mohamed Abouhawwash5,6,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2909-2924, 2023, DOI:10.32604/iasc.2023.030335 - 17 August 2022

    Abstract The main task of thyroid hormones is controlling the metabolism rate of humans, the development of neurons, and the significant growth of reproductive activities. In medical science, thyroid disorder will lead to creating thyroiditis and thyroid cancer. The two main thyroid disorders are hyperthyroidism and hypothyroidism. Many research works focus on the prediction of thyroid disorder. To improve the accuracy in the classification of thyroid disorder this paper proposes optimization-based feature selection by using differential evolution with the Butterfly optimization algorithm (DE-BOA). For the classifier fuzzy C-means algorithm (FCM) is used. The proposed DEBOA-FCM is More >

  • Open Access

    ARTICLE

    Convergence Track Based Adaptive Differential Evolution Algorithm (CTbADE)

    Qamar Abbas1, Khalid Mahmood Malik2, Abdul Khader Jilani Saudagar3,*, Muhammad Badruddin Khan3, Mozaherul Hoque Abul Hasanat3, Abdullah AlTameem3, Mohammed AlKhathami3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1229-1250, 2022, DOI:10.32604/cmc.2022.024211 - 24 February 2022

    Abstract One of the challenging problems with evolutionary computing algorithms is to maintain the balance between exploration and exploitation capability in order to search global optima. A novel convergence track based adaptive differential evolution (CTbADE) algorithm is presented in this research paper. The crossover rate and mutation probability parameters in a differential evolution algorithm have a significant role in searching global optima. A more diverse population improves the global searching capability and helps to escape from the local optima problem. Tracking the convergence path over time helps enhance the searching speed of a differential evolution algorithm… More >

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