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Training Multi-Layer Perceptron with Enhanced Brain Storm Optimization Metaheuristics

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Computers, Materials & Continua 2022年第2期70卷 4199-4215页

作者： Nebojsa Bacanin khaled alhazmi Miodrag Zivkovic K.Venkatachalam Timea Bezdan Jamel Nebhen Singidunum University Danijelova11000BelgradeSerbia National Center for Robotics and IoT Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh12371Saudi Arabia Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Prince Sattam Bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia

In the domain of artificial neural networks,the learning process represents one of the most challenging *** the classification accuracy highly depends on theweights and biases,it is crucial to find its optimal or suboptimal values for the problem at ***,to a very large search space,it is very difficult to find the proper values of connection weights and *** traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local *** commonly,back-propagation is used formulti-layer-perceptron training and it can lead to vanishing gradient *** an alternative approach,stochastic optimization algorithms,such as nature-inspired metaheuristics are more reliable for complex optimization tax,such as finding the proper values of weights and biases for neural network *** thiswork,we propose an enhanced brain storm optimization-based algorithm for training neural *** the simulations,ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization *** results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-theart approaches on the majority of datasets in terms of classification accuracy and convergence speed,due to the capability of balancing the intensification and diversification and avoiding the local *** proposed approach obtained the best accuracy on eight out of ten observed dataset,outperforming all other algorithms by 1-2%on *** mean accuracy is observed,the proposed algorithm dominated on nine out of ten datasets.

关键词： Artificial neural network optimization metaheuristics algorithm hybridization brain storm optimization

Fuzzy Control Based Resource Scheduling in IoT Edge Computing

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Computers, Materials & Continua 2022年第6期71卷 4855-4870页

作者： Samah alhazmi Kailash Kumar Soha Alhelaly College of Computing and Informatics Saudi Electronic UniversityRiyadhKingdom of Saudi Arabia

Edge Computing is a new technology in Internet of Things(IoT)paradigm that allows sensitive data to be sent to disperse devices quickly and without *** is identical to Fog,except its positioning in the end devices is much nearer to end-users,making it process and respond to clients in less ***,it aids sensor networks,real-time streaming apps,and the IoT,all of which require high-speed and dependable internet *** such an IoT system,Resource Scheduling Process(RSP)seems to be one of the most important *** paper presents a RSP for Edge Computing(EC).The resource characteristics are first standardized and ***,for task scheduling,a Fuzzy Control based Edge Resource Scheduling(FCERS)is *** results demonstrate that this technique enhances resource scheduling efficiency in EC and Quality of Service(QoS).The experimental study revealed that the suggested FCERS method in this work converges quicker than the other *** method reduces the total computing cost,execution time,and energy consumption on average compared to the *** ES allocates higher processing resources to each user in case of limited availability of MDs;this results in improved task execution time and a reduced total task computation ***,the proposed FCERS m 1m may more efficiently fetch user requests to suitable resource categories,increasing user requirements.

关键词： IoT edge computing resource scheduling task scheduling fuzzy control

Advanced control solutions for enhanced resilience of modern power-electronic-interfaced distribution systems

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Journal of Modern Power Systems and Clean Energy 2019年第4期7卷 716-730页

作者： Shiyuan WANG Payman DEHGHANIAN Mohannad alhazmi Mostafa NAZEMI Department of Electrical and Computer Engineering George Washington UniversityWashington 20052USA

Modern power delivery systems are rapidly evolving with high proliferation of power-electronic(PE)-interfaced distributed energy resources(DERs).Compared to the conventional sources of generation,the PE-interfaced DERs,e.g.,solar and wind resources,are attributed to substantially different characteristics such as lower overload capability and limited frequency response *** paper focuses on effective management and control mechanisms for PE-interfaced DERs in power distribution systems with high penetration of renewables,particularly vailing conditions in the *** enhance the system performance resilience,we introduce an advanced model predictive control(MPC)based scheme to control the DER units,minimize the impact of transients and disruptions,speed up the response and recovery of particular metrics and parameters,and maintain an acceptable operation *** performance of the suggested control scheme is tested on a modified IEEE 34-bus test feeder,where the proposed solution demonstrates its effectiveness to minimize the system transient during faults,with an enhanced grid-edge and system-wide resilience characteristics in voltage profiles.

关键词： Distributed energy resource(DER) Model predictive control(MPC) Power electronics(PE) Protection Resilience

Two-sided regularization model based on probabilistic matrix factorization and quantum similarity for recommender systems

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International Journal of Modeling, Simulation, and Scientific Computing 2020年第6期11卷 129-160页

作者： Waleed Reafee Marwa alhazmi Naomie Salim Faculty of Computer Studies and Information Technology University of Garden City 11111 KhartoumSudan School of Computing Faculty of Engineering Universiti Teknologi Malaysia81310 SkudaiJohorMalaysia

Nowadays,with the advent of the age of Web 2.0,several social recommendation methods that use social network information have been proposed and achieved distinct develop***,the most critical challenges for the existing majority of these methods are:(1)They tend to utilize only the available social relation between users and deal just with the cold-start user issue.(2)Besides,these methods are suffering from the lack of exploitation of content information such as social tagging,which can provide various sources to extract the item information to overcome the cold-start item and improve the recommendation *** this paper,we investigated the efficiency of data fusion by integrating multi-source of ***,two essential factors,user-side information,and item-side information,are ***,we developed a novel social recommendation model called Two-Sided Regularization(TSR),which is based on the probabilistic matrix factorization ***,the effective quantum-based similarity method is adapted to measure the similarity between users and between items into the proposed *** results on the real dataset show that our proposed model TSR addresses both of cold-start user and item issues and outperforms state-ofthe-art recommendation *** results indicate the importance of incorporating various sources of information in the recommendation process.

关键词： Social recommendation explicit friendship implicit friendship correlated items quantum mechanics

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Intelligent Automation & Soft Computing 2023年第6期36卷 3487-3499页

作者： Samah alhazmi Shahnawaz Khan Mohammad Haider Syed College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia Country Bahrain Polytechnic Isa Town33349Bahrain

Quality education is one of the primary objectives of any nation-build-ing strategy and is one of the seventeen Sustainable Development Goals(SDGs)by the United *** provide quality education,delivering top-quality con-tent is not ***,understanding the learners’emotions during the learning process is equally ***,most of this research work uses general data accessed from Twitter or other publicly available *** databases are generally not an ideal representation of the actual learning process and the learners’sentiments about the learning *** research has col-lected real data from the learners,mainly undergraduate university students of dif-ferent regions and *** analyzing the emotions of the students,appropriate steps can be suggested to improve the quality of education they *** order to understand the learning emotions,the XLNet technique is *** investigated the transfer learning method to adopt an efficient model for learners’sentiment detection and classification based on real *** experiment on the collected data shows that the proposed approach outperforms aspect enhanced sentiment analysis and topic sentiment analysis in the online learning community.

关键词： Transfer learning AI modeling optimization sentiment analysis deep learning

A Multi-Stage Secure IoT Authentication Protocol

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Computer Systems Science & Engineering 2023年第4期45卷 459-481页

作者： Khalid Alhusayni Raniyah Wazirali Mousa AlAkhras Marwah Almasri Samah alhazmi College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia King Abdullah II School for Information Technology The University of JordanAmman11942Jordan

The Internet of Things(IoT)is a network of heterogeneous and smart devices that can make decisions without human *** can connect millions of devices across the *** ability to collect information,perform analysis,and even come to meaningful conclusions without human capital intervention *** circumstances require stringent security measures and,in particular,the extent of *** applied in the IoT paradigm point out high-interest levels since enormous damage will occur if a malicious,wrongly authenticated device finds its way into the IoT *** research provides a clear and updated view of the trends in the IoT authentication *** the issues covered include a series of authentication protocols that have remained research gaps in various *** study applies a comparative evaluation of authentication protocols,including their strengths and ***,it forms the foundation in the IoT authentication field of *** that direction,a multi authentication architecture that involves secured means is proposed for protocol *** analysis can affect the security of the ***-Abadi-Needham(BAN)logic provides proof of the attainment of mutual ***3 simulator tool is used to compare the performance of the proposed protocol to verify the formal security offered by the BAN logic.

关键词： Internet of Things(IoT) security authentication BAN logic sensor networks

Advanced Optimized Anomaly Detection System for IoT Cyberattacks Using Artificial Intelligence

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Computers, Materials & Continua 2024年第2期78卷 1525-1545页

作者： Ali Hamid Farea Omar H.alhazmi Kerem Kucuk Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Department of Software Engineering Kocaeli UniversityKocaeli41001Turkey

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 *** 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 *** contribute to this nascent research stream,a novel AI-driven security system denoted as“AI2AI”is presented in this ***2AI employs AI techniques to enhance the performance and optimize security mechanisms within the IoT *** also introduce the Genetic Algorithm Anomaly Detection and Prevention Deep Neural Networks(GAADPSDNN)sys-tem that can be implemented to effectively identify,detect,and prevent cyberattacks targeting IoT ***,this system demonstrates adaptability to both federated and centralized learning environments,accommodating a wide array of IoT *** evaluation of the GAADPSDNN system using the recently complied WUSTL-IIoT and Edge-IIoT datasets underscores its *** an impressive overall accuracy of 98.18%on the Edge-IIoT dataset,the GAADPSDNN outperforms the standard deep neural network(DNN)classifier with 94.11%***,with the proposed enhancements,the accuracy of the unoptimized random forest classifier(80.89%)is improved to 93.51%,while the overall accuracy(98.18%)surpasses the results(93.91%,94.67%,94.94%,and 94.96%)achieved when alternative systems based on diverse optimization techniques and the same dataset are *** proposed optimization techniques increase the effectiveness of the anomaly detection system by efficiently achieving high accuracy and reducing the computational load on IoT devices through the adaptive selection of active features.

关键词： Internet of Things security anomaly detection and prevention system artificial intelligence optimization techniques

Selecting Best Software Vulnerability Scanner Using Intuitionistic Fuzzy Set TOPSIS

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Computers, Materials & Continua 2022年第8期72卷 3613-3629页

作者： Navneet Bhatt Jasmine Kaur Adarsh Anand Omar H.alhazmi Anil Surendra Modi School of Commerce Narsee Monjee Institute of Management StudiesDeemed to be UniversityMumbai400056India Department of Operational Research Faculty of Mathematical SciencesUniversity of DelhiDelhi110007India Department of Computer Science Taibah UniversityMedina30001Saudi Arabia

Software developers endeavor to build their products with the least number of *** this,many vulnerabilities are detected in software that threatens its *** automated software i.e.,vulnerability scanners,are available in the market which helps detect and manage vulnerabilities in a computer,application,or a ***,the choice of an appropriate vulnerability scanner is crucial to ensure efficient vulnerability *** current work serves a dual purpose,first,to identify the key factors which affect the vulnerability discovery process in a *** second,is to rank the popular vulnerability scanners based on the identified *** will aid the firm in determining the best scanner for them considering multiple *** multi-criterion decision making based ranking approach has been discussed using the Intuitionistic Fuzzy set(IFS)and Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)to rank the various *** IFS TOPSIS,the opinion of a whole group could be simultaneously considered in the vulnerability scanner *** this study,five popular vulnerability scanners,namely,Nessus,Fsecure Radar,Greenbone,Qualys,and Nexpose have been *** inputs of industry specialists i.e.,people who deal in software security and vulnerability management process have been taken for the ranking *** the proposed methodology,a hierarchical classification of the various vulnerability scanners could be *** clear enumeration of the steps allows for easy adaptability of the model to varied *** study will help product developers become aware of the needs of the market and design better *** from the user’s point of view,it will help the system administrators in deciding which scanner to deploy depending on the company’s needs and *** current work is the first to use a Multi Criterion Group Decision Making technique in vulnerability scanner selection.

关键词： Intuitionistic fuzzy set group decision making multi-criteria decision making(MCDM) ranking algorithm software security TOPSIS vulnerability vulnerability scanners

Optimal Sprint Length Determination for Agile-Based Software Development

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Computers, Materials & Continua 2021年第9期68卷 3693-3712页

作者： Adarsh Anand Jasmine Kaur Ompal Singh Omar H.alhazmi Department of Operational Research University of DelhiDelhi110007India Department of Computer Science Taibah UniversityMedina30001Saudi Arabia

A carefully planned software development process helps in maintaining the quality of the *** today’s scenario the primitive software development models have been replaced by the Agile based models like SCRUM,KANBAN,LEAN,***,every framework has its own boon,the reason for widespread acceptance of the agile-based approach is its evolutionary nature that permits change in the path of software *** development process occurs in iterative and incremental cycles called *** SCRUM,which is one of the most widely used agile-based software development modeling framework;the sprint length is fixed throughout the process wherein;it is usually taken to be 1–4 *** in practical application,the sprint length should be altered intuitively as per the *** overcome this limitation,in this paper,a methodical work has been presented that determines the optimal sprint length based on two varied and yet connected attributes;the cost incurred and the work intensity *** approach defines the number of tasks performed in each sprint along with the corresponding cost incurred in performing those ***-attribute utility theory(MAUT),a multi-criterion decision making approach,has been utilized to find the required trade-off between two attributes under *** proposed modeling framework has been validated using real life data *** the use of the model,the optimal sprint for each sprint could be evaluated which was much shorter than the original ***,the results obtained validate the proposal of a dynamic sprint length that can be determined before the start of each *** structure would help in cost as well as time savings for a firm.

关键词： Agile principles agile-based software development dynamic sprint length multi-attribute utility theory scrum software development life cycle