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  • Open Access

    ARTICLE

    Efficient Hybrid Energy Optimization Method in Location Aware Unmanned WSN

    M. Suresh Kumar1,*, G. A. Sathish Kumar2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 705-725, 2023, DOI:10.32604/iasc.2023.027545 - 06 June 2022

    Abstract The growth of Wireless Sensor Networks (WSNs) has revolutionized the field of technology and it is used in different application frameworks. Unmanned edges and other critical locations can be monitored using the navigation sensor node. The WSN required low energy consumption to provide a high network and guarantee the ultimate goal. The main objective of this work is to propose hybrid energy optimization in local aware environments. The hybrid proposed work consists of clustering, optimization, direct and indirect communication and routing. The aim of this research work is to provide and framework for reduced energy More >

  • Open Access

    ARTICLE

    Black Widow Optimization for Multi Area Economic Emission Dispatch

    G. Girishkumar1,*, S. Ganesan2, N. Jayakumar3, S. Subramanian4

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 609-625, 2023, DOI:10.32604/iasc.2023.027514 - 06 June 2022

    Abstract The optimization field has grown tremendously, and new optimization techniques are developed based on statistics and evolutionary procedures. Therefore, it is necessary to identify a suitable optimization technique for a particular application. In this work, Black Widow Optimization (BWO) algorithm is introduced to minimize the cost functions in order to optimize the Multi-Area Economic Dispatch (MAED). The BWO is implemented for two different-scale test systems, comprising 16 and 40 units with three and four areas. The performance of BWO is compared with the available optimization techniques in the literature to demonstrate the strategy’s efficacy. Results More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization with Artificial Neural Network Based Robust Paddy Yield Prediction Model

    S. Muthukumaran1,*, P. Geetha2, E. Ramaraj1

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 215-230, 2023, DOI:10.32604/iasc.2023.027449 - 06 June 2022

    Abstract Agriculture plays a vital role in the food production process that occupies nearly one-third of the total surface of the earth. Rice is propagated from the seeds of paddy and it is a stable food almost used by fifty percent of the total world population. The extensive growth of the human population alarms us to ensure food security and the country should take proper food steps to improve the yield of food grains. This paper concentrates on improving the yield of paddy by predicting the factors that influence the growth of paddy with the help… More >

  • Open Access

    ARTICLE

    Novel Block Chain Technique for Data Privacy and Access Anonymity in Smart Healthcare

    J. Priya*, C. Palanisamy

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 243-259, 2023, DOI:10.32604/iasc.2023.025719 - 06 June 2022

    Abstract The Internet of Things (IoT) and Cloud computing are gaining popularity due to their numerous advantages, including the efficient utilization of internet and computing resources. In recent years, many more IoT applications have been extensively used. For instance, Healthcare applications execute computations utilizing the user’s private data stored on cloud servers. However, the main obstacles faced by the extensive acceptance and usage of these emerging technologies are security and privacy. Moreover, many healthcare data management system applications have emerged, offering solutions for distinct circumstances. But still, the existing system has issues with specific security issues,… More >

  • Open Access

    ARTICLE

    Hybrid Convolutional Neural Network and Long Short-Term Memory Approach for Facial Expression Recognition

    M. N. Kavitha1,*, A. RajivKannan2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 689-704, 2023, DOI:10.32604/iasc.2023.025437 - 06 June 2022

    Abstract Facial Expression Recognition (FER) has been an important field of research for several decades. Extraction of emotional characteristics is crucial to FERs, but is complex to process as they have significant intra-class variances. Facial characteristics have not been completely explored in static pictures. Previous studies used Convolution Neural Networks (CNNs) based on transfer learning and hyperparameter optimizations for static facial emotional recognitions. Particle Swarm Optimizations (PSOs) have also been used for tuning hyperparameters. However, these methods achieve about 92 percent in terms of accuracy. The existing algorithms have issues with FER accuracy and precision. Hence,… 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 - 16 May 2023

    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… 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 More >

  • Open Access

    ARTICLE

    An Adaptive BWO Algorithm with RSA for Anomaly Detection in VANETs

    Y. Sarada Devi*, M. Roopa

    Journal of Cyber Security, Vol.4, No.3, pp. 153-167, 2022, DOI:10.32604/jcs.2022.033436 - 01 February 2023

    Abstract Vehicular ad hoc networks (VANETs) are designed in accordance with the ad hoc mobile networks (MANETs), i.e., impulsive formation of a wireless network for V2V (vehicle-to-vehicle) communication. Each vehicle is preserved as a node which remains as share of network. All the vehicle in the network is made to be under communication in a VANET because of which all the vehicles in the range can be made connected to a to a unit & a wide network can be established with a huge range. Healthier traffic management, vehicle-to-vehicle communication and provision of road information can… More >

  • Open Access

    ARTICLE

    Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

    Rongxin Zhang1,*, Chengying Yang2,3, Xuetao Li1

    Energy Engineering, Vol.119, No.6, pp. 2489-2511, 2022, DOI:10.32604/ee.2022.021517 - 14 September 2022

    Abstract Buildings are the main energy consumers across the world, especially in urban communities. Building smartization, or the smartification of housing, therefore, is a major step towards energy grid smartization too. By controlling the energy consumption of lighting, heating, and cooling systems, energy consumption can be optimized. All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources (RES), which mitigates environmental impacts and reduces peak demand for electrical energy. In this paper, a new optimization algorithm is applied to solve the optimal energy consumption problem by considering… More >

  • Open Access

    ARTICLE

    Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

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

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5771-5788, 2022, DOI:10.32604/cmc.2022.032229 - 28 July 2022

    Abstract Metamaterial Antennas are a type of antenna that uses metamaterial to enhance performance. The bandwidth restriction associated with small antennas can be solved using metamaterial antennas. Machine learning is gaining popularity as a way to improve solutions in a range of fields. Machine learning approaches are currently a big part of current research, and they’re likely to be huge in the future. The model utilized determines the accuracy of the prediction in large part. The goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and gain. The… More >

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