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Search Results (9)
  • Open Access

    ARTICLE

    Advanced Optimized Anomaly Detection System for IoT Cyberattacks Using Artificial Intelligence

    Ali Hamid Farea1,*, Omar H. Alhazmi1, Kerem Kucuk2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1525-1545, 2024, DOI:10.32604/cmc.2023.045794

    Abstract While emerging technologies such as the Internet of Things (IoT) have many benefits, they also pose considerable security challenges that require innovative solutions, including those based on artificial intelligence (AI), given that these techniques are increasingly being used by malicious actors to compromise IoT systems. Although an ample body of research focusing on conventional AI methods exists, there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures. To contribute to this nascent research stream, a novel AI-driven security system denoted as “AI2AI” is presented in this work. AI2AI employs AI techniques to… More >

  • Open Access

    REVIEW

    Economic Power Dispatching from Distributed Generations: Review of Optimization Techniques

    Paramjeet Kaur1, Krishna Teerth Chaturvedi1, Mohan Lal Kolhe2,*

    Energy Engineering, Vol.121, No.3, pp. 557-579, 2024, DOI:10.32604/ee.2024.043159

    Abstract In the increasingly decentralized energy environment, economical power dispatching from distributed generations (DGs) is crucial to minimizing operating costs, optimizing resource utilization, and guaranteeing a consistent and sustainable supply of electricity. A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability. The choice of optimization technique for economic power dispatching from DGs depends on a number of factors, such as the size and complexity of the power system, the availability of computational resources, and the specific requirements of the… More >

  • Open Access

    ARTICLE

    An Optimized Deep Learning Approach for Improving Airline Services

    Shimaa Ouf*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1213-1233, 2023, DOI:10.32604/cmc.2023.034399

    Abstract The aviation industry is one of the most competitive markets. The most common approach for airline service providers is to improve passenger satisfaction. Passenger satisfaction in the aviation industry occurs when passengers’ expectations are met during flights. Airline service quality is critical in attracting new passengers and retaining existing ones. It is crucial to identify passengers’ pain points and enhance their satisfaction with the services offered. The airlines used a variety of techniques to improve service quality. They used data analysis approaches to analyze the passenger point data. These solutions have focused simply on surveys; consequently, deep-learning approaches have received… More >

  • Open Access

    ARTICLE

    Optimization Techniques in University Timetabling Problem: Constraints, Methodologies, Benchmarks, and Open Issues

    Abeer Bashab1, Ashraf Osman Ibrahim2,*, Ibrahim Abakar Tarigo Hashem3, Karan Aggarwal4, Fadhil Mukhlif5, Fuad A. Ghaleb5, Abdelzahir Abdelmaboud6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6461-6484, 2023, DOI:10.32604/cmc.2023.034051

    Abstract University timetabling problems are a yearly challenging task and are faced repeatedly each semester. The problems are considered non-polynomial time (NP) and combinatorial optimization problems (COP), which means that they can be solved through optimization algorithms to produce the aspired optimal timetable. Several techniques have been used to solve university timetabling problems, and most of them use optimization techniques. This paper provides a comprehensive review of the most recent studies dealing with concepts, methodologies, optimization, benchmarks, and open issues of university timetabling problems. The comprehensive review starts by presenting the essence of university timetabling as NP-COP, defining and clarifying the… More >

  • Open Access

    ARTICLE

    Optimization of Head Cluster Selection in WSN by Human-Based Optimization Techniques

    Hajer Faris1, Musaria Karim Mahmood2, Osama Ahmad Alomari3,*, Ashraf Elnagar4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5643-5661, 2022, DOI:10.32604/cmc.2022.026228

    Abstract Wireless sensor networks (WSNs) are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data, and transmit it in a collaborative manner to one or more processing centers wirelessly using a routing protocol. Energy dissipation is one of the most challenging issues due to the limited power supply at the sensor node. All routing protocols are large consumers of energy, as they represent the main source of energy cost through data exchange operation. Cluster-based hierarchical routing algorithms are known for their good performance in energy conservation during active data exchange in… More >

  • Open Access

    ARTICLE

    Energy Theft Identification Using Adaboost Ensembler in the Smart Grids

    Muhammad Irfan1,*, Nasir Ayub2, Faisal Althobiani3, Zain Ali4, Muhammad Idrees5, Saeed Ullah2, Saifur Rahman1, Abdullah Saeed Alwadie1, Saleh Mohammed Ghonaim3, Hesham Abdushkour3, Fahad Salem Alkahtani1, Samar Alqhtani6, Piotr Gas7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2141-2158, 2022, DOI:10.32604/cmc.2022.025466

    Abstract One of the major concerns for the utilities in the Smart Grid (SG) is electricity theft. With the implementation of smart meters, the frequency of energy usage and data collection from smart homes has increased, which makes it possible for advanced data analysis that was not previously possible. For this purpose, we have taken historical data of energy thieves and normal users. To avoid imbalance observation, biased estimates, we applied the interpolation method. Furthermore, the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing. By proposing an improved version… More >

  • Open Access

    ARTICLE

    Prediction of Transformer Oil Breakdown Voltage with Barriers Using Optimization Techniques

    Sherif S. M. Ghoneim1,*, Mosleh M. Alharthi1, Ragab A. El-Sehiemy2, Abdullah M. Shaheen3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1593-1610, 2022, DOI:10.32604/iasc.2022.020464

    Abstract A new procedure to optimally identifying the prediction equation of oil breakdown voltage with the barrier parameters’ effect is presented. The specified equation is built based on the results of experimental works to link the response with the barrier parameters as the inputs for hemisphere-hemisphere electrode gap configuration under AC voltage. The AC HV is applied using HV Transformer Type (PGK HB-100 kV AC) to the high voltage electrode in the presence of a barrier immersed in Diala B insulating oil. The problem is formulated as a nonlinear optimization problem to minimize the error between experimental and estimated breakdown voltages… More >

  • Open Access

    ARTICLE

    Personalized Nutrition Recommendation for Diabetic Patients Using Optimization Techniques

    Bhavithra Janakiraman1,*, Saradha Arumugam2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 269-280, 2020, DOI:10.31209/2019.100000150

    Abstract Personalization in recommendation system has been emerging as the most predominant area in service computing. Collaborative filtering and content based approaches are two major techniques applied for recommendation. However, to improve the accuracy and enhance user satisfaction, optimization techniques such as Ant Colony and Particle Swarm Optimization were analyzed in this paper. For theoretical analysis, this paper investigates web page recommender system. For experimentation, Diabetic patient’s health records were investigated and recommendation algorithms are applied to suggest appropriate nutrition for improving their health. Experiment result shows that Particle Swarm Optimization outperforms other traditional methods with improved performance and accuracy. More >

  • Open Access

    ARTICLE

    The Design of Multi-Element Airfoils Through Multi-Objective Optimization Techniques

    G. Trapani1, T. Kipouros1, A. M. Savill1

    CMES-Computer Modeling in Engineering & Sciences, Vol.88, No.2, pp. 107-140, 2012, DOI:10.3970/cmes.2012.088.107

    Abstract This paper presents the development and the application of a multi-objective optimization framework for the design of two-dimensional multi-element high-lift airfoils. An innovative and efficient optimization algorithm, namely Multi-Objective Tabu Search (MOTS), has been selected as core of the framework. The flow-field around the multi-element configuration is simulated using the commercial computational fluid dynamics (cfd) suite Ansys cfx. Elements shape and deployment settings have been considered as design variables in the optimization of the Garteur A310 airfoil, as presented here. A validation and verification process of the cfd simulation for the Garteur airfoil is performed using available wind tunnel data.… More >

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