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  • Open Access

    ARTICLE

    Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNN Model

    Qi Zhuang1,*, Dong Liu2, Zhuo Chen3

    Energy Engineering, Vol.121, No.3, pp. 821-834, 2024, DOI:10.32604/ee.2023.044054

    Abstract Oil and gas pipelines are affected by many factors, such as pipe wall thinning and pipeline rupture. Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management. Aiming at the shortcomings of the BP Neural Network (BPNN) model, such as low learning efficiency, sensitivity to initial weights, and easy falling into a local optimal state, an Improved Sparrow Search Algorithm (ISSA) is adopted to optimize the initial weights and thresholds of BPNN, and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established. Taking 61 sets More >

  • Open Access

    ARTICLE

    Research on Evacuation Path Planning Based on Improved Sparrow Search Algorithm

    Xiaoge Wei1,2,*, Yuming Zhang1,2, Huaitao Song1,2, Hengjie Qin1,2, Guanjun Zhao3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1295-1316, 2024, DOI:10.32604/cmes.2023.045096

    Abstract Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years. As part of this effort, an enhanced sparrow search algorithm (MSSA) was proposed. Firstly, the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm. Secondly, the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima. Finally, the local search mechanism based on the mountain climbing method was incorporated into… More >

  • Open Access

    ARTICLE

    An Improved BPNN Prediction Method Based on Multi-Strategy Sparrow Search Algorithm

    Xiangyan Tang1,2, Dengfang Feng2,*, KeQiu Li1, Jingxin Liu2, Jinyang Song3, Victor S. Sheng4

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2789-2802, 2023, DOI:10.32604/cmc.2023.031304

    Abstract Data prediction can improve the science of decision-making by making predictions about what happens in daily life based on natural law trends. Back propagation (BP) neural network is a widely used prediction method. To reduce its probability of falling into local optimum and improve the prediction accuracy, we propose an improved BP neural network prediction method based on a multi-strategy sparrow search algorithm (MSSA). The weights and thresholds of the BP neural network are optimized using the sparrow search algorithm (SSA). Three strategies are designed to improve the SSA to enhance its optimization-seeking ability, leading More >

  • Open Access

    ARTICLE

    An ISSA-RF Algorithm for Prediction Model of Drug Compound Molecules Antagonizing ERα Gene Activity

    Minxi Rong1, Yong Li1,*, Xiaoli Guo1,*, Tao Zong2, Zhiyuan Ma2, Penglei Li2

    Oncologie, Vol.24, No.2, pp. 309-327, 2022, DOI:10.32604/oncologie.2022.021256

    Abstract Objectives: The ERα biological activity prediction model is constructed by the compound molecular data of the anti-breast cancer therapeutic target ERα and its biological activity data, which improves the screening efficiency of anti-breast cancer drug candidates and saves the time and cost of drug development. Methods: In this paper, Ridge model is used to screen out molecular descriptors with a high degree of influence on the biological activity of Erα and divide datasets with different numbers of the molecular descriptors by screening results. Random Forest (RF) is trained by Root Mean Square Error (RMSE) and Coefficient of… More >

  • Open Access

    ARTICLE

    Brain Tumor Diagnosis Using Sparrow Search Algorithm Based Deep Learning Model

    G. Ignisha Rajathi1, R. Ramesh Kumar2, D. Ravikumar3, T. Joel4, Seifedine Kadry4,5, Chang-Won Jeong6, Yunyoung Nam7,*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1793-1806, 2023, DOI:10.32604/csse.2023.024674

    Abstract Recently, Internet of Medical Things (IoMT) has gained considerable attention to provide improved healthcare services to patients. Since earlier diagnosis of brain tumor (BT) using medical imaging becomes an essential task, automated IoMT and cloud enabled BT diagnosis model can be devised using recent deep learning models. With this motivation, this paper introduces a novel IoMT and cloud enabled BT diagnosis model, named IoMTC-HDBT. The IoMTC-HDBT model comprises the data acquisition process by the use of IoMT devices which captures the magnetic resonance imaging (MRI) brain images and transmit them to the cloud server. Besides,… More >

  • Open Access

    ARTICLE

    A Chaos Sparrow Search Algorithm with Logarithmic Spiral and Adaptive Step for Engineering Problems

    Andi Tang, Huan Zhou*, Tong Han, Lei Xie

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 331-364, 2022, DOI:10.32604/cmes.2021.017310

    Abstract The sparrow search algorithm (SSA) is a newly proposed meta-heuristic optimization algorithm based on the sparrow foraging principle. Similar to other meta-heuristic algorithms, SSA has problems such as slow convergence speed and difficulty in jumping out of the local optimum. In order to overcome these shortcomings, a chaotic sparrow search algorithm based on logarithmic spiral strategy and adaptive step strategy (CLSSA) is proposed in this paper. Firstly, in order to balance the exploration and exploitation ability of the algorithm, chaotic mapping is introduced to adjust the main parameters of SSA. Secondly, in order to improve… More >

  • Open Access

    ARTICLE

    An Improved Sparrow Search Algorithm for Node Localization in WSN

    R. Thenmozhi1, Abdul Wahid Nasir2, Vijaya Krishna Sonthi3, T. Avudaiappan4, Seifedine Kadry5, Kuntha Pin6, Yunyoung Nam7,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2037-2051, 2022, DOI:10.32604/cmc.2022.022203

    Abstract Wireless sensor networks (WSN) comprise a set of numerous cheap sensors placed in the target region. A primary function of the WSN is to avail the location details of the event occurrences or the node. A major challenge in WSN is node localization which plays an important role in data gathering applications. Since GPS is expensive and inaccurate in indoor regions, effective node localization techniques are needed. The major intention of localization is for determining the place of node in short period with minimum computation. To achieve this, bio-inspired algorithms are used and node localization… More >

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