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  • Open Access

    ARTICLE

    Frequency Control Approach and Load Forecasting Assessment for Wind Systems

    K. Sukanya*, P. Vijayakumar

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 971-982, 2023, DOI:10.32604/iasc.2023.028047

    Abstract Frequency deviation has to be controlled in power generation units when there are fluctuations in system frequency. With several renewable energy sources, wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature. Whenever there is a mismatch between generation and demand, the frequency deviation may arise from the actual frequency 50 Hz (in India). To mitigate the frequency deviation issue, it is necessary to develop an effective technique for better frequency control in wind energy systems. In this work, heuristic Fuzzy Logic Based Controller (FLC) is developed for providing… More >

  • Open Access

    ARTICLE

    Enhanced Sentiment Analysis Algorithms for Multi-Weight Polarity Selection on Twitter Dataset

    Ayman Mohamed Mostafa*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1015-1034, 2023, DOI:10.32604/iasc.2023.028041

    Abstract Sentiment analysis is based on the orientation of user attitudes and satisfaction towards services and subjects. Different methods and techniques have been introduced to analyze sentiments for obtaining high accuracy. The sentiment analysis accuracy depends mainly on supervised and unsupervised mechanisms. Supervised mechanisms are based on machine learning algorithms that achieve moderate or high accuracy but the manual annotation of data is considered a time-consuming process. In unsupervised mechanisms, a lexicon is constructed for storing polarity terms. The accuracy of analyzing data is considered moderate or low if the lexicon contains small terms. In addition, most research methodologies analyze datasets… More >

  • Open Access

    ARTICLE

    Encryption with User Authentication Model for Internet of Medical Things Environment

    K. S. Riya1, R. Surendran2,*, Carlos Andrés Tavera Romero3, M. Sadish Sendil4

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 507-520, 2023, DOI:10.32604/iasc.2023.027779

    Abstract Internet of Medical Things (IoMT) enabled e-healthcare has the potential to greately improve conventional healthcare services significantly. However, security and privacy become major issues of IoMT because of the restricted processing abilities, storage, and energy constraints of the sensors. Therefore, it leads to infeasibility of developing traditional cryptographic solutions to the IoMT sensors. In order to ensure security on sensitive medical data, effective encryption and authentication techniques need to be designed to assure security of the patients and healthcare service providers. In this view, this study designs an effective metaheuristic optimization based encryption with user authentication (EMOE-UA) technique for IoMT… More >

  • Open Access

    ARTICLE

    Deep Learning Based Autonomous Transport System for Secure Vehicle and Cargo Matching

    T. Shanthi1,*, M. Ramprasath2, A. Kavitha3, T. Muruganantham4

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 957-969, 2023, DOI:10.32604/iasc.2023.027775

    Abstract The latest 6G improvements secured autonomous driving's realism in Intelligent Autonomous Transport Systems (IATS). Despite the IATS's benefits, security remains a significant challenge. Blockchain technology has grown in popularity as a means of implementing safe, dependable, and decentralised independent IATS systems, allowing for more utilisation of legacy IATS infrastructures and resources, which is especially advantageous for crowdsourcing technologies. Blockchain technology can be used to address security concerns in the IATS and to aid in logistics development. In light of the inadequacy of reliance and inattention to rights created by centralised and conventional logistics systems, this paper discusses the creation of… More >

  • Open Access

    ARTICLE

    Timer Entrenched Baited Scheme to Locate and Remove Attacks in MANET

    S. Padmapriya1, R. Shankar2, R. Thiagarajan1,*, N. Partheeban3, A. Daniel3, S. Arun4

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 491-505, 2023, DOI:10.32604/iasc.2023.027719

    Abstract The Mobile Ad-hoc Network (MANET) is a dynamic topology that provides a variety of executions in various disciplines. The most sticky topic in organizational fields was MANET protection. MANET is helpless against various threats that affect its usability and accessibility. The dark opening assault is considered one of the most far-reaching dynamic assaults that deteriorate the organization's execution and reliability by dropping all approaching packages via the noxious node. The Dark Opening Node aims to deceive any node in the company that wishes to connect to another node by pretending to get the most delicate ability to support the target… More >

  • Open Access

    ARTICLE

    Creating Smart House via IoT and Intelligent Computation

    Wen-Tsai Sung1, Sung-Jung Hsiao2,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 415-430, 2023, DOI:10.32604/iasc.2023.027618

    Abstract This study mainly uses the concept of the Internet of Things (IoT) to establish a smart house with an indoor, comfortable, environmental, and real-time monitoring system. In the smart house, this investigation employed the temperature- and humidity-sensing module and the lightness module to monitor any condition for an intelligent-living house. The data of temperature, humidity, and lightness are transmitted wirelessly to the human-machine interface. The correlation of the weight of the extension theory is used to analyze the ideal and comfortable environment so that people in the indoor environment can feel better thermal comfort and lightness. In this study, improved… More >

  • Open Access

    ARTICLE

    Vision Navigation Based PID Control for Line Tracking Robot

    Rihem Farkh*, Khaled Aljaloud

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 901-911, 2023, DOI:10.32604/iasc.2023.027614

    Abstract In a controlled indoor environment, line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots. A line tracking robot is a self-mobile machine that can recognize and track a painted line on the floor. In general, the path is set and can be visible, such as a black line on a white surface with high contrasting colors. The robot’s path is marked by a distinct line or track, which the robot follows to move. Several scientific contributions from the disciplines of vision and control have been made to mobile robot vision-based navigation. Localization, automated map… More >

  • Open Access

    ARTICLE

    P-ROCK: A Sustainable Clustering Algorithm for Large Categorical Datasets

    Ayman Altameem1, Ramesh Chandra Poonia2, Ankit Kumar3, Linesh Raja4, Abdul Khader Jilani Saudagar5,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 553-566, 2023, DOI:10.32604/iasc.2023.027579

    Abstract Data clustering is crucial when it comes to data processing and analytics. The new clustering method overcomes the challenge of evaluating and extracting data from big data. Numerical or categorical data can be grouped. Existing clustering methods favor numerical data clustering and ignore categorical data clustering. Until recently, the only way to cluster categorical data was to convert it to a numeric representation and then cluster it using current numeric clustering methods. However, these algorithms could not use the concept of categorical data for clustering. Following that, suggestions for expanding traditional categorical data processing methods were made. In addition to… More >

  • Open Access

    ARTICLE

    An Optimized Algorithm for Renewable Energy Forecasting Based on Machine Learning

    Ziad M. Ali1,2,*, Ahmed M. Galal1,3, Salem Alkhalaf4, Imran Khan5

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 755-767, 2023, DOI:10.32604/iasc.2023.027568

    Abstract The large-scale application of renewable energy power generation technology brings new challenges to the operation of traditional power grids and energy management on the load side. Microgrid can effectively solve this problem by using its regulation and flexibility, and is considered to be an ideal platform. The traditional method of computing total transfer capability is difficult due to the central integration of wind farms. As a result, the differential evolution extreme learning machine is offered as a data mining approach for extracting operating rules for the total transfer capability of tie-lines in wind-integrated power systems. K-medoids clustering under the two-dimensional… More >

  • Open Access

    ARTICLE

    Data Aggregation-based Transmission Method in Ultra-Dense Wireless Networks

    Dae-Young Kim, Seokhoon Kim*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 727-737, 2023, DOI:10.32604/iasc.2023.027563

    Abstract As the Internet of Things (IoT) advances, machine-type devices are densely deployed and massive networks such as ultra-dense networks (UDNs) are formed. Various devices attend to the network to transmit data using machine-type communication (MTC), whereby numerous, various are generated. MTC devices generally have resource constraints and use wireless communication. In this kind of network, data aggregation is a key function to provide transmission efficiency. It can reduce the number of transmitted data in the network, and this leads to energy saving and reducing transmission delays. In order to effectively operate data aggregation in UDNs, it is important to select… More >

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