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  • Open Access

    ARTICLE

    Managing Software Testing Technical Debt Using Evolutionary Algorithms

    Muhammad Abid Jamil*, Mohamed K. Nour

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 735-747, 2022, DOI:10.32604/cmc.2022.028386 - 18 May 2022

    Abstract Technical debt (TD) happens when project teams carry out technical decisions in favor of a short-term goal(s) in their projects, whether deliberately or unknowingly. TD must be properly managed to guarantee that its negative implications do not outweigh its advantages. A lot of research has been conducted to show that TD has evolved into a common problem with considerable financial burden. Test technical debt is the technical debt aspect of testing (or test debt). Test debt is a relatively new concept that has piqued the curiosity of the software industry in recent years. In this… More >

  • Open Access

    ARTICLE

    Evolutionary Intelligence and Deep Learning Enabled Diabetic Retinopathy Classification Model

    Bassam A. Y. Alqaralleh1,*, Fahad Aldhaban1, Anas Abukaraki2, Esam A. AlQaralleh3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 87-101, 2022, DOI:10.32604/cmc.2022.026729 - 18 May 2022

    Abstract Diabetic Retinopathy (DR) has become a widespread illness among diabetics across the globe. Retinal fundus images are generally used by physicians to detect and classify the stages of DR. Since manual examination of DR images is a time-consuming process with the risks of biased results, automated tools using Artificial Intelligence (AI) to diagnose the disease have become essential. In this view, the current study develops an Optimal Deep Learning-enabled Fusion-based Diabetic Retinopathy Detection and Classification (ODL-FDRDC) technique. The intention of the proposed ODL-FDRDC technique is to identify DR and categorize its different grades using retinal More >

  • Open Access

    ARTICLE

    Evolutionary Algorithm Based Z-Source DC-DC Boost Converter for Charging EV Battery

    P. Anitha1, K. Karthik Kumar2,*, M. Ravindran2, A. Saravanaselvan2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1377-1397, 2022, DOI:10.32604/iasc.2022.025396 - 03 May 2022

    Abstract In this paper, efficient charging of electric vehicle battery from a considered renewable solar photovoltaic source with the help of a modified Z source with efficient boosting topology. Adapting this Z-source converter to act as a voltage gainer with a boosting function allows a solar Photovoltaic (PV) input voltage of 25VDC (Volts Direct Current) to be increased to a designed output voltage of 75VDC at a low duty ratio, resulting in minimal switching loss. The closed-loop steady-state and transient parameters at the output were analyzed and compared using modern evolutionary algorithms. The power range upheld… More >

  • Open Access

    ARTICLE

    Evolutionary Algorithm Based Adaptive Load Balancing (EA-ALB) in Cloud Computing Framework

    J. Noorul Ameen1,*, S. Jabeen Begum2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1281-1294, 2022, DOI:10.32604/iasc.2022.025137 - 03 May 2022

    Abstract In the present decade, the development of cloud computing framework is witnessed for providing computational resources by dynamic service providing methods. There are many problems in load balancing in cloud, when there is a huge demand for resources. The objective of load balancing is to equilibrate the cloud server computations for avoiding overloading problems. On addressing the issue, this paper develops a new model called Evolutionary Algorithm based Adaptive Load Balancing (EA-ALB) for enhancing the efficacy and user satisfaction of cloud services. Efficient Scheduling Scheme for the virtual machines using machine learning algorithm is proposed More >

  • Open Access

    ARTICLE

    MDA-TOEPGA: A novel method to identify miRNA-disease association based on two-objective evolutionary programming genetic algorithm

    BUWEN CAO1,*, JIAWEI LUO2,*, SAINAN XIAO1,2, XIANGJUN ZHOU1

    BIOCELL, Vol.46, No.8, pp. 1925-1933, 2022, DOI:10.32604/biocell.2022.019613 - 22 April 2022

    Abstract The association between miRNA and disease has attracted more and more attention. Until now, existing methods for identifying miRNA related disease mainly rely on top-ranked association model, which may not provide a full landscape of association between miRNA and disease. Hence there is strong need of new computational method to identify the associations from miRNA group view. In this paper, we proposed a framework, MDA-TOEPGA, to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm, which identifies latent miRNAdisease associations from the view of functional module. To understand the miRNA functional module in diseases, More >

  • Open Access

    ARTICLE

    Evolutionary Algorithsm with Machine Learning Based Epileptic Seizure Detection Model

    Manar Ahmed Hamza1,*, Noha Negm2, Shaha Al-Otaibi3, Amel A. Alhussan4, Mesfer Al Duhayyim5, Fuad Ali Mohammed Al-Yarimi2, Mohammed Rizwanullah1, Ishfaq Yaseen1

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4541-4555, 2022, DOI:10.32604/cmc.2022.027048 - 21 April 2022

    Abstract Machine learning (ML) becomes a familiar topic among decision makers in several domains, particularly healthcare. Effective design of ML models assists to detect and classify the occurrence of diseases using healthcare data. Besides, the parameter tuning of the ML models is also essential to accomplish effective classification results. This article develops a novel red colobuses monkey optimization with kernel extreme learning machine (RCMO-KELM) technique for epileptic seizure detection and classification. The proposed RCMO-KELM technique initially extracts the chaotic, time, and frequency domain features in the actual EEG signals. In addition, the min-max normalization approach is More >

  • Open Access

    ARTICLE

    MLP-PSO Framework with Dynamic Network Tuning for Traffic Flow Forecasting

    V. Rajalakshmi1,*, S. Ganesh Vaidyanathan2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1335-1348, 2022, DOI:10.32604/iasc.2022.024310 - 24 March 2022

    Abstract Traffic flow forecasting is the need of the hour requirement in Intelligent Transportation Systems (ITS). Various Artificial Intelligence Frameworks and Machine Learning Models are incorporated in today’s ITS to enhance forecasting. Tuning the model parameters play a vital role in designing an efficient model to improve the reliability of forecasting. Hence, the primary objective of this research is to propose a novel hybrid framework to tune the parameters of Multilayer Perceptron (MLP) using the Swarm Intelligence technique called Particle Swarm Optimization (PSO). The proposed MLP-PSO framework is designed to adjust the weights and bias parameters… More >

  • Open Access

    ARTICLE

    Insight into the characteristics of an important evolutionary model bird (Geospiza magnirostris) mitochondrial genome through comparison

    ZHENGGANG XU1,2,3, LIANG WU3, JIAHAO CHEN1, YUNLIN ZHAO3, CHONGXUAN HAN1, TIAN HUANG2, GUIYAN YANG1,*

    BIOCELL, Vol.46, No.7, pp. 1733-1746, 2022, DOI:10.32604/biocell.2022.015784 - 17 March 2022

    Abstract Darwin’s finches are the most classic case of evolution. Early studies on the evolution of this species were mainly based on morphology. Until now, the mitochondrial genome of Geospiza magnirostris has been sequenced and the study explored the characteristics of the complete genome of G. magnirostris and verified the evolutionary position of it. The 13 PCGs initiated by ATN codons. The stop codons of three PCGs (ND2, COX3 and ND4) were incomplete, with only T- or TA- replacing complete form TAA or TAG. All the tRNA genes expressed a typical cloverleaf secondary structure, except for tRNASer1(AGY), whose dihydrouridine (DHU)… More >

  • Open Access

    ARTICLE

    An Evolutionary Normalization Algorithm for Signed Floating-Point Multiply-Accumulate Operation

    Rajkumar Sarma1, Cherry Bhargava2, Ketan Kotecha3,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 481-495, 2022, DOI:10.32604/cmc.2022.024516 - 24 February 2022

    Abstract In the era of digital signal processing, like graphics and computation systems, multiplication-accumulation is one of the prime operations. A MAC unit is a vital component of a digital system, like different Fast Fourier Transform (FFT) algorithms, convolution, image processing algorithms, etcetera. In the domain of digital signal processing, the use of normalization architecture is very vast. The main objective of using normalization is to perform comparison and shift operations. In this research paper, an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer, Adder etc. The… More >

  • Open Access

    ARTICLE

    Differential Evolution Algorithm with Hierarchical Fair Competition Model

    Amit Ramesh Khaparde1,*, Fawaz Alassery2, Arvind Kumar3, Youseef Alotaibi4, Osamah Ibrahim Khalaf5, Sofia Pillai6, Saleh Alghamdi7

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1045-1062, 2022, DOI:10.32604/iasc.2022.023270 - 08 February 2022

    Abstract This paper presents the study of differential evolution algorithm with hierarchical fair competition model (HFC-DE). HFC model is based on the fair competition of societal system found in natural world. In this model, the population is split into hierarchy and the competition is allowed between the hierarchical members. During evolution, the population members are allowed to move within the hierarchy levels. The standard differential evolution algorithm is used for population evolution. Experimentation has carried out to define the parameter for proposed model on test suit having unimodal problems and multi-model problems. After analyzing the results, More >

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