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An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

Computers, materials & Continua 2022年第7期72卷 1995-2014页

作者： mutasem K.Alsmadi Ghaith m.Jaradat malek Alzaqebah Ibrahim A.Lmarashdeh Fahad A.Alghamdi Rami mustafa A.mohammad Nahier Aldhafferi Abdullah Alqahtani Department of mIS College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Department of Computer Science Faculty of Computer Science and InformaticsAmman Arab UniversityAmmanJordan Department of mathematics College of ScienceImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Basic and Applied Scientific Research CenterImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Computer Information Systems Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia

Timetabling problem is among the most difficult operational tasks and is an important step in raising industrial productivity,capability,and *** tasks are usually tackled using metaheuristics techniques that provide an intelligent way of suggesting solutions or *** intelligence techniques including Particle Swarm Optimization(PSO)have proved to be effective *** recent experiments showed that the PSO algorithm is reliable for timetabling in many applications such as educational and personnel timetabling,machine scheduling,***,having an optimal solution is extremely challenging but having a sub-optimal solution using heuristics or metaheuristics is *** research paper seeks the enhancement of the PSO algorithm for an efficient timetabling *** algorithm aims at generating a feasible timetable within a reasonable *** enhanced version is a hybrid dynamic adaptive PSO algorithm that is tested on a round-robin tournament known as ITC2021 which is dedicated to sports *** competition includes several soft and hard constraints to be satisfied in order to build a feasible or sub-optimal *** consists of three categories of complexities,namely early,test,and middle *** showed that the proposed dynamic adaptive PSO has obtained feasible timetables for almost all of the *** feasibility is measured by minimizing the violation of hard constraints to *** performance of the dynamic adaptive PSO is evaluated by the consumed computational time to produce a solution of feasible timetable,consistency,and *** dynamic adaptive PSO showed a robust and consistent performance in producing a diversity of timetables in a reasonable computational time.

关键词： Sports timetabling particle swarm optimization ITC2021 roundrobin tournament dynamic adaptive

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Effect of Lorentz forces on forced-convection nanofluid flow over a stretched surface

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Particuology 2016年第3期14卷 108-113页

作者： mohsen Sheikholeslami m.T. mustafa Davood Domiri Ganji Department of mechanical Engineering Babol University of Technology Babol Islamic Republic oflran Department of mathematics Statistics and Physics Qatar University Doha 2713 Qatar

magnetic nanofiuid hydrothermal analysis over a plate is studied that includes consideration of thermal radiation. The Runge-Kutta （RK4） method is utilized to get solution of ODEs which are obtained from similarity solution. In considering the impacts of Brownian motion, we applied Koo-Kleinstreuer-Li cor- relation to simulate the properties of CuO-water. The influence is discussed of important parameters such as the temperature index, magnetic, radiation, and velocity ratio parameters and volume fraction of nanoparticle on hydrothermal behavior. Results illustrate that the coefficient of skin friction enhances with enhancing magnetic parameter while reduces with enhancing velocity ratio parameter. Also the Nusselt number was found to directly depend on the velocity ratio and temperature index parameters but has an inverse dependence on the magnetic and radiation parameters.

关键词： Nanofluid Brownian motion Thermal radiation magnetohydrodynamic Stretching sheet

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Analytical study of Cattaneo–Christov heat flux model for a boundary layer flow of Oldroyd-B fluid

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Chinese Physics B 2016年第1期25卷 657-662页

作者： F m Abbasi m mustafa S A Shehzad m S Alhuthali T Hayat Department of mathematics Comsats Institute of lnformaHon TechnologyIslamabad 44000Pakistan School of Natural Sciences(SNS) National University of Science and Technology(NUST)Islamabad 44000Pakistan Department of mathematics Comsats Institute of/nformation TechnologySahiwa157000Pakistan NAAm Research Group Department of MathematicsFaculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of mathematics Quaid-I-Azam University 45320Islamabad 44000Pakistan

We investigate the Cattaneo-Christov heat flux model for a two-dimensional laminar boundary layer flow of an incompressible Oldroyd-B fluid over a linearly stretching sheet. mathematical formulation of the boundary layer problems is given. The nonlinear partial differential equations are converted into the ordinary differential equations using similarity transformatioris. The dimensionless velocity and temperature profiles are obtained through optimal homotopy analysis method （OHAm）. The influences of the physical parameters on the velocity and the temperature are pointed out. The results show that the temperature and the thermal boundary layer thickness are smaller in the Cattaneo-Christov heat flux model than those in the Fourier＇s law of heat conduction.

关键词： Oldroyd-B fluid Cattaneo-Christov heat flux nonlinear analysis

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modeling of Artificial Intelligence Based Traffic Flow Prediction with Weather Conditions

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Computers, materials & Continua 2022年第5期71卷 3953-3968页

作者： mesfer Al Duhayyim Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Hiba m.Burbur mohammad Alamgeer Anwer mustafa Hilal manar Ahmed Hamza mohammed Rizwanullah Department of Natural and Applied Sciences College of Community-AflajPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Computer Science College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer Science College of Science and Arts in Al-BukairiyahQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Information Systems College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Short-term traffic flow prediction (TFP) is an important area inintelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodicfeatures are susceptible to weather conditions, making TFP a challengingissue. TFP process are significantly influenced by several factors like accidentand weather. Particularly, the inclement weather conditions may have anextreme impact on travel time and traffic flow. Since most of the existing TFPtechniques do not consider the impact of weather conditions on the TF, it isneeded to develop effective TFP with the consideration of extreme weatherconditions. In this view, this paper designs an artificial intelligence based TFPwith weather conditions (AITFP-WC) for smart cities. The goal of the AITFPWC model is to enhance the performance of the TFP model with the inclusionof weather related conditions. The proposed AITFP-WC technique includesElman neural network (ENN) model to predict the flow of traffic in smartcities. Besides, tunicate swarm algorithm with feed forward neural networks(TSA-FFNN) model is employed for the weather and periodicity analysis. Atlast, a fusion of TFP and WPA processes takes place using the FFNN modelto determine the final prediction output. In order to assess the enhancedpredictive outcome of the AITFP-WC model, an extensive simulation analysisis carried out. The experimental values highlighted the enhanced performanceof the AITFP-WC technique over the recent state of art methods.

关键词： Smart cities artificial intelligence urban transportation deep learning weather condition TFP

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manta Ray Foraging Optimization with machine Learning Based Biomedical Data Classification

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Computers, materials & Continua 2022年第11期73卷 3275-3290页

作者： Amal Al-Rasheed Jaber S.Alzahrani majdy m.Eltahir Abdullah mohamed Anwer mustafa Hilal Abdelwahed motwakel Abu Sarwar Zamani mohamed I.Eldesouki Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The biomedical data classification process has received significant attention in recent times due to a massive increase in the generation of healthcare data from various *** developments of artificial intelligence(AI)and machine learning(mL)models assist in the effectual design of medical data classification ***,this article concentrates on the development of optimal Stacked Long Short Term memory Sequence-toSequence Autoencoder(OSAE-LSTm)model for biomedical data *** presented OSAE-LSTm model intends to classify the biomedical data for the existence of ***,the OSAE-LSTm model involves min-max normalization based pre-processing to scale the data into uniform *** by,the SAE-LSTm model is utilized for the detection and classification of diseases in biomedical *** last,manta ray foraging optimization(mRFO)algorithm has been employed for hyperparameter optimization *** utilization of mRFO algorithm assists in optimal selection of hypermeters involved in the SAE-LSTm *** simulation analysis of the OSAE-LSTm model has been tested using a set of benchmark medical datasets and the results reported the improvements of the OSAELSTm model over the other approaches under several dimensions.

关键词： Biomedical data classification deep learning manta ray foraging optimization healthcare machine learning artificial intelligence

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An Investigation on the Formation of Submerged Bar Under Surges in Sandy Coastal Region

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China Ocean Engineering 2012年第3期26卷 535-546页

作者： mustafa DEmIRCI m.Sami AKZ Civil Engineering Department Engineering FacultyMustafa Kemal UniversityskenderunHatay 31040Turkey Civil Engineering Department Engineering and Architecture Facultyukurova UniversityAdana 01100Turkey

Cross-shore sediment transport rate exposed to waves is very important for coastal morphology, the design of marine structures such as seawalls, jetties, breakwaters etc, and the prevention of coastal erosion and accretion due to onoff shore sediment transportation. In the present study, the experiments on cross-shore sediment transport are carried out in a laboratory wave channel with initial beach slopes of 1/8, 1/10 and 1/15. By using the regular waves with different deep-water wave steepnesses generated by a pedal-type wave generator, the geometrical characteristics of beach profiles under storm conditions and the parameters affecting on-off shore sediment transport are investigated for the beach materials with medium diameters of d50=0.25, 0.32, 0.45, 0.62 and 0.80 mm. The offshore bar geometric characteristics are the horizontal distances from the shoreline to the bar beginning （Xb）, crest （Xt）, and ending （Xs） points, the depth from the bar crest to the still water level （ht）, and the bar volume （Vbar）. The experimental results have indicated that when the deep-water steepness （Ha/L0） increased, the net movement to seaside increased. With the increasing wave steepness, the bars moved to widen herewith the vertical distances from still water level to the bar beginning （Xb）, crest （Xt） and ending （Xs） points and the horizontal distances from the coast line to the bar beginning, crest and ending points increased. It was also shown from experimental results that the horizontal distances from the bar beginning and ending points to the coast line increased with the decrease of the beach slope. The experimental results obtained from this study are compared with previous experimental work and found to be of the same magnitude as the experimental measurements and followed the expected basic trend.

关键词： cross-shore sediment transport beach profiles bar parameters experimental study

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Systematic Investigation of Two-Phase Flow in Special Channels

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Fluid Dynamics & materials Processing 2022年第4期18卷 1039-1048页

作者： Oleg R.Kuzichkin muneam Hussein Ali Ayad F.Alkaim Lis m.Yapanto Gabdrakhman H.Valiev L.S.Abdullah mustafa m.Kadhim Department of Information and Robototechnic Systems Belgorod State UniversityBelgorod308015Russia Al-Nisour University College Baghdad10012Iraq College of Science for Women University of BabylonBabil51002Iraq Departement of Aquatic management Faculty of Fisheries and Marine Science Universitas Negeri GorontaloGorontalo96128Indonesia Kazan Federal University Kazan420008Russia Lipetsk State Technical University Lipetsk398600Russia Department of Dentistry Kut University CollegeKutWasit52001Iraq

A systematic study of two-phase(water-air)currents in open channels(water-air)has been conducted by means of experiments and numerical simulations.A dedicated device has been designed and manufactured on *** numerical simulations have been based on the solution of a system of mass,momentum and energy balance equations for a two-phase *** effect of different influential parameters has been explored,namely,velocity and dimensions of the channel,surface pressure and tension.

关键词： Two-phase special channels systematic study pressure drop

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Optimal Deep Learning Enabled Communication System for Unmanned Aerial Vehicles

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Computer Systems Science & Engineering 2023年第4期45卷 955-969页

作者： Anwer mustafa Hilal Jaber S.Alzahrani Dalia H.Elkamchouchi majdy m.Eltahir Ahmed S.Almasoud Abdelwahed motwakel Abu Sarwar Zamani Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia

Recently,unmanned aerial vehicles(UAV)or drones are widely employed for several application areas such as surveillance,disaster management,*** UAVs are limited to energy,efficient coordination between them becomes essential to optimally utilize the resources and effective communication among them and base station(BS).Therefore,clustering can be employed as an effective way of accomplishing smart communication systems among multiple *** this aspect,this paper presents a group teaching optimization algorithm with deep learning enabled smart communication system(GTOADL-SCS)technique for UAV *** proposed GTOADL-SCS model encompasses a two stage process namely clustering and *** the initial stage,the GTOADL-SCS model includes a GTOA based clustering scheme to elect cluster heads(CHs)and organize ***,the GTOADL-SCS model develops a fitness function containing three input parameters as residual energy of UAVs,average neighoring distance,and UAV *** classification process,the GTOADLSCS model applies pre-trained densely connected network(DenseNet201)feature extractor with gated recurrent unit(GRU)*** ensuring the enhanced performance of the GTOADL-SCS model,a widespread simulation analysis is performed and the comparative study reported the significant outcomes over the existing approaches with maximum packet delivery ratio(PDR)of 92.60%.

关键词： Unmanned aerial vehicles energy efficiency smart communication system deep learning

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An experimental and numerical study of chemically enhanced water alternating gas injection

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Petroleum Science 2015年第3期12卷 470-482页

作者： Saeed majidaie mustafa Onur Isa m.Tan Leap Energy-Subsurface Consulting Services Department of Petroleum and Natural Gas Engineering Istanbul Technical University Applied Science Department Universiti Teknologi Petronas

In this work, an experimental study combined with numerical simulation was conducted to investigate the potential of chemically enhanced water alternating gas （CWAG） injection as a new enhanced oil recovery method. The unique feature of this new method is that it uses alkaline, surfactant, and polymer additives as a chemical slug which is injected during the water alternating gas （WAG） process to reduce the interfacial tension （IFT） and simultaneously improve the mobility ratio. In essence, the proposed CWAG process involves a combination of chemical flooding and immiscible carbon dioxide （CO2） injection and helps in IFT reduction, water blocking reduction, mobility control, oil swelling, and oil viscosity reduction due to CO2 dissolution. Its performance was compared with the conventional immiscible water alter- nating gas （I-WAG） flooding. Oil recovery utilizing CWAG was better by 26 % of the remaining oil in place after waterflooding compared to the recovery using WAG conducted under similar conditions. The coreflood data （cumulative oil and water production） were history mat- ched via a commercial simulator by adjusting the relative permeability curves and assigning the values of the rock and fluid properties such as porosity, permeability, and the experimentally determined IFT data. History matching ofthe coreflood model helped us optimize the experiments and was useful in determining the importance of the parameters influencing sweep efficiency in the CWAG process. The effectiveness of the CWAG process in pro- viding enhancement of displacement efficiency is evident in the oil recovery and pressure response observed in the coreflood. The results of sensitivity analysis on CWAG slug patterns show that the alkaline-surfactant-polymer injection is more beneficial after CO2 slug injection due to oil swelling and viscosity reduction. The CO2 slug size analysis shows that there is an optimum CO2 slug size, around 25 % pore volume which leads to a maximum oil recover

关键词： Enhanced water alternating gas (CWAG) Enhanced oil recovery Interfacial tension mobilitycontrol ~ Water blocking

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Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis model

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Computer Systems Science & Engineering 2023年第5期45卷 1129-1143页

作者： Anwer mustafa Hilal Eatedal Alabdulkreem Jaber S.Alzahrani majdy m.Eltahir mohamed I.Eldesouki Ishfaq Yaseen Abdelwahed motwakel Radwa marzouk Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of mathematics Faculty of ScienceCairo UniversityGiza12613Egypt

Biomedical image processing is widely utilized for disease detection and classification of biomedical *** color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and *** removing the qualitative aspect,tongue images are quantitatively inspected,proposing a novel disease classification model in an automated way is *** article introduces a novel political optimizer with deep learning enabled tongue color image analysis(PODL-TCIA)*** presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the *** attain this,the PODL-TCIA model initially performs image pre-processing to enhance medical image *** by,Inception with ResNet-v2 model is employed for feature ***,political optimizer(PO)with twin support vector machine(TSVm)model is exploited for image classification process,shows the novelty of the *** design of PO algorithm assists in the optimal parameter selection of the TSVm *** ensuring the enhanced outcomes of the PODL-TCIA model,a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.

关键词： Tongue color image analysis political optimizer twin support vector machine inception model deep learning

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