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  • Open Access

    ARTICLE

    Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

    Hassan Shokouhandeh1, Mehrdad Ahmadi Kamarposhti2,*, William Holderbaum3, Ilhami Colak4, Phatiphat Thounthong5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 809-822, 2023, DOI:10.32604/csse.2023.035827

    Abstract The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the energy supply cost with the… More >

  • Open Access

    ARTICLE

    Web Intelligence with Enhanced Sunflower Optimization Algorithm for Sentiment Analysis

    Abeer D. Algarni*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1233-1247, 2023, DOI:10.32604/csse.2022.026915

    Abstract Exponential increase in the quantity of user generated content in websites and social networks have resulted in the emergence of web intelligence approaches. Several natural language processing (NLP) tools are commonly used to examine the large quantity of data generated online. Particularly, sentiment analysis (SA) is an effective way of classifying the data into different classes of user opinions or sentiments. The latest advances in machine learning (ML) and deep learning (DL) approaches offer an intelligent way of analyzing sentiments. In this view, this study introduces a web intelligence with enhanced sunflower optimization based deep learning model for sentiment analysis… More >

  • Open Access

    ARTICLE

    T_GRASP: Optimization Algorithm of Ship Avoiding Typhoon Route

    Yingxian Huang, Xueyan Ding, Yanan Zhang, Leiming Yan*

    Journal of Quantum Computing, Vol.4, No.2, pp. 85-95, 2022, DOI:10.32604/jqc.2022.031436

    Abstract A GRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation. One of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a typhoon. Currently, the captains manually review the collected weather data and steer clear of typhoons using their navigational expertise. The distribution of heavy winds and waves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution, which significantly enhances the challenge of the captain’s preparation for avoiding typhoon navigation. It is now… More >

  • Open Access

    ARTICLE

    An Efficient Approach Based on Remora Optimization Algorithm and Levy Flight for Intrusion Detection

    Abdullah Mujawib Alashjaee*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 235-254, 2023, DOI:10.32604/iasc.2023.036247

    Abstract With the recent increase in network attacks by threats, malware, and other sources, machine learning techniques have gained special attention for intrusion detection due to their ability to classify hundreds of features into normal system behavior or an attack attempt. However, feature selection is a vital preprocessing stage in machine learning approaches. This paper presents a novel feature selection-based approach, Remora Optimization Algorithm-Levy Flight (ROA-LF), to improve intrusion detection by boosting the ROA performance with LF. The developed ROA-LF is assessed using several evaluation measures on five publicly available datasets for intrusion detection: Knowledge discovery and data mining tools competition,… More >

  • Open Access

    ARTICLE

    Improved Harris Hawks Optimization Algorithm Based Data Placement Strategy for Integrated Cloud and Edge Computing

    V. Nivethitha*, G. Aghila

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 887-904, 2023, DOI:10.32604/iasc.2023.034247

    Abstract Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows. The individual tasks of a scientific workflow necessitate a diversified number of large states that are spatially located in different datacenters, thereby resulting in huge delays during data transmission. Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets. Therefore, this fixed storage strategy creates huge amount of bottleneck in its storage capacity. At this juncture, integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and… More >

  • Open Access

    ARTICLE

    Modeling of Combined Economic and Emission Dispatch Using Improved Sand Cat Optimization Algorithm

    Fadwa Alrowais1, Jaber S. Alzahrani2, Radwa Marzouk1, Abdullah Mohamed3, Gouse Pasha Mohammed4,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6145-6160, 2023, DOI:10.32604/cmc.2023.038300

    Abstract Combined Economic and Emission Dispatch (CEED) task forms multi-objective optimization problems to be resolved to minimize emission and fuel costs. The disadvantage of the conventional method is its incapability to avoid falling in local optimal, particularly when handling nonlinear and complex systems. Metaheuristics have recently received considerable attention due to their enhanced capacity to prevent local optimal solutions in addressing all the optimization problems as a black box. Therefore, this paper focuses on the design of an improved sand cat optimization algorithm based CEED (ISCOA-CEED) technique. The ISCOA-CEED technique majorly concentrates on reducing fuel costs and the emission of generation… More >

  • Open Access

    ARTICLE

    A Whale Optimization Algorithm with Distributed Collaboration and Reverse Learning Ability

    Zhedong Xu*, Yongbo Su, Fang Yang, Ming Zhang

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5965-5986, 2023, DOI:10.32604/cmc.2023.037611

    Abstract Due to the development of digital transformation, intelligent algorithms are getting more and more attention. The whale optimization algorithm (WOA) is one of swarm intelligence optimization algorithms and is widely used to solve practical engineering optimization problems. However, with the increased dimensions, higher requirements are put forward for algorithm performance. The double population whale optimization algorithm with distributed collaboration and reverse learning ability (DCRWOA) is proposed to solve the slow convergence speed and unstable search accuracy of the WOA algorithm in optimization problems. In the DCRWOA algorithm, the novel double population search strategy is constructed. Meanwhile, the reverse learning strategy… More >

  • Open Access

    ARTICLE

    Improved Monarchy Butterfly Optimization Algorithm (IMBO): Intrusion Detection Using Mapreduce Framework Based Optimized ANU-Net

    Kunda Suresh Babu, Yamarthi Narasimha Rao*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5887-5909, 2023, DOI:10.32604/cmc.2023.037486

    Abstract The demand for cybersecurity is rising recently due to the rapid improvement of network technologies. As a primary defense mechanism, an intrusion detection system (IDS) was anticipated to adapt and secure computing infrastructures from the constantly evolving, sophisticated threat landscape. Recently, various deep learning methods have been put forth; however, these methods struggle to recognize all forms of assaults, especially infrequent attacks, because of network traffic imbalances and a shortage of aberrant traffic samples for model training. This work introduces deep learning (DL) based Attention based Nested U-Net (ANU-Net) for intrusion detection to address these issues and enhance detection performance.… More >

  • Open Access

    ARTICLE

    PREDICTION MODEL OF WAX DEPOSITION RATE BASED ON WOABPNN ALGORITHM

    Rongge Xiaoa,* , Qi Zhuanga, Shuaishuai Jina , Wenbo Jina

    Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-7, 2022, DOI:10.5098/hmt.18.8

    Abstract A model for predicting wax deposition rate in pipeline transportation is constructed to predict wax deposition in actual pipeline, which can provide decision support for the flow guarantee of waxy crude oil in pipeline transportation. This paper analyzes the working principle of Back Propagation Neural Networks (BPNN). Aiming at the problems of BPNN model, such as over learning, long training time, low generalization ability and easy to fall into local minimum, the paper proposes an improved scheme of using Whale Optimization Algorithm (WOA) to optimize BPNN model(WOABPNN).Taking 38 groups of crude oil wax deposition experimental data in Huachi operation area… More >

  • Open Access

    ARTICLE

    PREDICTION MODEL OF LIQUID HOLDUP BASED ON SOA-BPNN ALGORITHM

    Qi Zhuanga,* , Dong Liub, Bo Liuc, Mei Liua

    Frontiers in Heat and Mass Transfer, Vol.20, pp. 1-6, 2023, DOI:10.5098/hmt.20.13

    Abstract In the actual operation of wet gas pipeline, liquid accumulation is easy to form in the low-lying and uphill sections of the pipeline, which leads to a series of problems such as reduced pipeline transportation efficiency, increased pipeline pressure drop, hydrate formation, slug flow and intensified corrosion in the pipeline. Accurate calculation of liquid holdup is of great significance to the research of flow pattern identification, pipeline corrosion evaluation and prediction, and gas pipeline transportation efficiency calculation. Based on the experimental data of liquid holdup in horizontal pipeline, a commonly used BP neural network (BPNN) model is established in this… More >

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