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14th International Conference Management of Large-Scale System Development, MLSD 2021

作者： Ereshko, Felix Gorelov, Mikhail Federal Research Center 'Computer Science and Control' Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (纸本)9781665412308

The paper examines a new class of models, the common feature of which is the presence of a limited volume of information exchanges between players. It is shown that taking such restrictions into account allows one to significantly expand the class of situations that can be adequately described using the games in normal form. Possible ways of formalizing the concept of 'amount of information' are discussed, returning to the constructions by A.N. Kolmogorov. A new concept of the maximal guaranteed result is discussed. The application of the outlined ideas in the information theory of hierarchical systems is considered. © 2021 IEEE.

关键词： Hierarchical systems

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Analysis of the Russian Agricultural Research Organizations' Digital Footprint 14

Analysis of the Russian Agricultural Research Organizations'...

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14th International Conference Management of Large-Scale System Development, MLSD 2021

作者： Medennikov, Viktor Flerov, Yuri Federal Research Center 'Computer Science and Control Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (纸本)9781665412308

This work analyzes domestic agricultural research organizations' ratings shaped by applying methodologies of generating such ratings with consideration to active, passive, and semiactive digital footprints in the internet space. A mathematical description of the methodologies is provided. The benchmarking analysis of the resulting ratings is presented. © 2021 IEEE.

关键词： Agriculture

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Hybrid Dipper Throated and Grey Wolf Optimization for Feature Selection Applied to Life Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4531-4545页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Mostafa Abotaleb Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.

关键词： Metaheuristics dipper throated optimization grey wolf optimization binary optimizer feature selection

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Classification of information Objects with Fuzzy Parameters in E-Learning systems 12

Classification of Information Objects with Fuzzy Parameters ...

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12th IEEE International Conference on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications, IDAACS 2023

作者： Mukhin, Vadym Zavgorodnii, Valerii Liskin, Viacheslav Syrota, Sergiy Koval, Vasyl Honchar, Liudmyla National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of System Design Kiev Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Information Systems and Technologies Kiev Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Applied Mathematics Kiev Ukraine West Ukrainian National University Department of Information-Computing Systems and Control Ternopil Ukraine West Ukrainian National University Department of Computer Science Ternopil Ukraine

ISBN: (纸本)9798350358056

The paper describes the process of the information objects classification in e-learning systems using the mathematical background of fuzzy logic. This approach can be used to improve the process of searching and organizing information in e-learning systems. As the volume of educational materials grows, it becomes more and more difficult to find and structure information. Fuzzy logic helps to optimize the search, and the use of a neural network can correctly classify materials in e-learning systems, which increases the efficiency and accuracy of search queries. © 2023 IEEE.

关键词： classification e-learning system fuzzy logic information object neural network

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Models of Battle Dynamics in Strategic Computer Games 16

Models of Battle Dynamics in Strategic Computer Games

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Laryushin, Ivan Dmitrievich Pashin, Dmitrii Sergeevich Koltochenko, Yaroslav Alekseevich Ereshko, Felix Ivanovich Gaponov-Grekhov Institute of Applied Physics Ras Plasma Physics Department Nizhny Novgorod Russia State University of Nizhny Novgorod Faculty of Physics National Research Lobachevsky Nizhny Novgorod Russia Moscow Institute of Physics and Technology Department of Mathematical Modeling of Complex Systems and Optimization Moscow Russia Federal Research Center 'Computer Science and Control' of the Ras Department of Information and Computing Systems Moscow Russia

ISBN: (纸本)9798350337907

A set of new models that describe the dynamics of battles in strategic computer games is presented. These models not only have descriptive functions, but also allow solving problems of optimizing army control under given conditions, as well as calculating the most efficient composition of the army for the planned operation within a computer game. © 2023 IEEE.

关键词： Computer games

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Improved Prediction of Metamaterial Antenna Bandwidth Using Adaptive Optimization of LSTM

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Computers, Materials & Continua 2022年第10期73卷 865-881页

作者： Doaa Sami Khafaga Amel Ali Alhussan El-Sayed M.El-kenawy Abdelhameed Ibrahim Said H.Abd Elkhalik Shady Y.El-Mashad Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Systems Engineering Faculty of Engineering at ShoubraBenha UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended *** this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial *** proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep *** optimized network is used to retrieve the metamaterial bandwidth given a set of *** addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.

关键词： Metamaterial antenna long short term memory(LSTM) guided whale optimization algorithm(Guided WOA) adaptive dynamic particle swarm algorithm(AD-PSO)

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Development of the Predictive control System for Ethylbenzene Dehydration 3

Development of the Predictive Control System for Ethylbenzen...

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3rd International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Popov, Alexey Tikhomirov, Sergey Neizvestny, Oleg Podvalny, Semyon Voronezh State University of Engineering Technologies Department of Information and Control Systems Voronezh Russia Voronezh State Technical University Department of Automated and Computing Systems Voronezh Russia

ISBN: (纸本)9781665439817

the article describes the application of the predictive functional control method in the synthesis of an automated control system for the ethylbenzene dehydrogenation. Based on the results of the control object system analysis, the choice of the control method has been justified, a review and assessment of the possibility of using various types of control devices have been carried out. Within the framework of the model-based design concept, a control system has been synthesized that implements predictive functional control (PFC) of the styrene concentration at the output from the first stage of the reactor block. Structural synthesis has been performed and an algorithm for the functioning of the control system has been developed. A complex of dynamic models describing heat exchange processes and physicochemical transformations occurring during the dehydrogenation of ethylbenzene has been used as a structural element for constructing a predicted trajectory of changes in the control and controlled parameters. The calculation of the control action has been carried out taking into account the inertia of the process equipment, the state parameters of the reactor's catalytic layer, the values of energy flows and concentrations of the components. A comparative analysis of the results of calculating transient processes for the main channel of the control system, obtained using a PID structure controller and a control device that implements the PFC control method, has been presented. It was found that the use of the proposed algorithm and control system allows for the on-line computation of control actions and timely compensation for the decrease in the activity of the reactor's catalytic layer, which, in turn, prevents the decrease in the yield of the target product below the preset value, and also increases the energy efficiency and productivity of the reactor plant. © 2021 IEEE.

关键词： Styrene

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Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

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Computer systems Science & Engineering 2023年第5期45卷 1469-1482页

作者： Doaa Sami Khafaga Amel Ali Alhussan Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mohamed Saber El-Sayed M.El-kenawy Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electronics and Communications Engineering Department Faculty of EngineeringDelta University for Science and TechnologyMansouraEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Arrhythmia has been classified using a variety of *** of the dynamic nature of electrocardiogram(ECG)data,traditional handcrafted approaches are difficult to execute,making the machine learning(ML)solutions more *** with cardiac arrhythmias can benefit from competent monitoring to save their *** arrhythmia classification and prediction have greatly improved in recent *** are a category of conditions in which the heart's electrical activity is abnormally rapid or *** year,it is one of the main reasons of mortality for both men and women,*** the classification of arrhythmias,this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors(KNN)*** proposed method makes advantage of the UCI repository,which has a 279-attribute high-dimensional cardiac arrhythmia *** proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s *** purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia *** method of comprehensive arrhythmia classification outperforms earlier methods presented in the *** achieved classification accuracy using the proposed approach is 99.8%.

关键词： Feature selection electrocardiogram metaheuristics dipper throated algorithm

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Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

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Computer systems Science & Engineering 2023年第6期45卷 2885-2899页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Fadwa Alrowais Mostafa Abotaleb Abdelhameed Ibrahim Doaa Sami Khafaga Department of Communications and Elecronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science F aculty of Computer and Infomation SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Progamming South Ual State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LSTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-Sutcliffe model eficiency(NSE),mean square error(MSE),root MSE(RMSE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LSTM,bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and convolutional LSTM(ConvLSTM).It was found that the proposed approach achieved the lowest RMSE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.

关键词： Rainfall prediction long short-term memory Al-Biruni earth radius algorithm meta-heuristic optimization

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Traffic Light control to Form Progressive Movements along an Arterial

Traffic Light Control to Form Progressive Movements along an...

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European control Conference (ECC)

作者： Weilin Wang Yanwei Zang Wenbiao Zhang Yang Xu Jiayuan Liang Hanran Zhang Lachlan Andrew Hai Vu Chaohui Gong Department of Control Science and Engineering University of Shanghai for Sciece and Technology Huadong Engineering Corporation Limited School of Computing and Information Systems University of Melbourne Institute of Transport Studies Monash University

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

A traffic light control protocol is proposed, which builds compact platoons of vehicles to make efficient use of green times. It forms short platoons at multiple links and times traffic lights to concatenate these to form a single dense platoon, in which vehicles mostly passes many intersections without stopping. The protocol minimizes the number of times vehicles stop; by simulation, it roughly halves that of greenwave under near saturated demand.

关键词： Protocols Roads Europe Vehicle dynamics Junctions

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