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Fuzzy modeling of Economic systems: Main problems 24

Fuzzy Modeling of Economic Systems: Main Problems

引用

24th international conference on Soft Computing and Measurements, SCM 2021

作者： Nedosekin, Alexey O. Abdoulaeva, Zinaida I. Vul, Olga A. Konnikov, Evgenii A. Saint Petersburg Russia

ISBN: (纸本)9781665439749

Purpose: Determine the main directions of promising scientific research in the field of fuzzy-multiple analysis of economic systems, implying three main problems: the influence of implicit organizational factors, modeling external disturbances and ensuring statistical homogeneity of the initial data. Method: modeling the implicit factors of economic systems is justified on the basis of the matrix aggregate calculator (MAC) technology. The same technology can be applied in adverse effects (AE) modeling, but with much less success, and complex hybrid descriptions must be used here. In the course of assessing the statistical homogeneity of input information flows, R-lenses have performed well. Result: The main ways of overcoming the considered scientific difficulties are demonstrated. Conclusions: Overcoming the identified problems effectively during the formation of interdisciplinary research teams. © 2021 IEEE.

关键词： Aggregates

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A study on maintenance scheduling and workforce planning under deep uncertainty 51

A study on maintenance scheduling and workforce planning und...

引用

51st international conference on Computers and Industrial Engineering, CIE 2024

作者： Kahagalage, Sanath Darshana Turan, Hasan Hüseyin Sharma, Pankaj Sawah, Sondoss El Capability Systems Centre University of New South Wales Canberra at ADFA Northcott Drive CampbellACT2600 Australia School of Business University of New South Wales Canberra at ADFA Northcott Drive CampbellACT2600 Australia

Most of the real-world problems often involve multiple conflicting objectives and many decision variables. However, most of the applications concern a single objective problem and/or decision variables in isolation. Decision-making, even under the most favorable circumstances, is made difficult enough by budget constraints, conflicting stakes, and political turmoil. So, every reduction in uncertainty is more than welcome;ignoring deep uncertainty is attractive. But decisions that ignore deep uncertainty ignore reality. Substituting assumptions for deep uncertainties might simplify choices in the short term but may come at a much higher price in the longer term. In this research, using a comprehensive real-life case study-based Discrete Event Simulation model, we address high-value asset maintenance, encompassing workforce and maintenance planning problem under the condition of deeply uncertain factors such as workforce separation and resource failures. Our objective is to identify robust solutions from a predefined set of strategies encompassing workforce and maintenance planning. Results guide decision-making by identifying robust strategies, identifying critical uncertain parameters and their ranges, and revealing vulnerable outcomes. Results highlight the significance of striking the right balance between maintenance and workforce planning. Results also reveals the importance of achieving a harmonious balance within the workforce plan. In conclusion, robust decision-making framework empowers decision-makers to navigate deep uncertainty, offering insights to support informed and robust decisions. © 2024 Computers and Industrial Engineering. All rights reserved.

关键词： Budget control

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Solution of Optimal Power Flow problems Using Enhanced Hunter Pray Optimization Algorithm

Solution of Optimal Power Flow Problems Using Enhanced Hunte...

引用

IEEE international conference on Power Electronics, Intelligent control and Energy systems (ICPEICES)

作者： Bimal Kumar Dora Sudip Halder Ruchita Sunil Waghmare Tarun Gangadhar Pranjali Kulkarni Sunil Bhat Electrical Engineering Department VNIT Nagpur Nagpur India

ISBN: (数字)9798350387193

ISBN: (纸本)9798350387209

This work presents a new algorithm specifically developed to solve the Optimal Active Power Dispatch (OAPD) problems. The OAPD problem aims to minimize total voltage deviation, quadratic fuel cost, and complex nonlinear fuel cost, while considering the impact of valve point loading (VPL) effects and prohibited operating zone (POZ). This is done to maintain an economically efficient operational condition in a power system. The proposed hybrid algorithm combines the non-uniform mutation process with the Hunter-Prey Optimization Algorithm (HPOA) in order to improve the local search capabilities of HPOA. HPOA manages the global search process, whereas non-uniform mutation process and HPOA operate together for local search process. This combined technique effectively addresses complex nonlinear optimization problems. The proposed method is applied to determine the optimal settings to minimize real power loss, simple quadratic fuel cost and the fuel cost with VPL and POZ. The IEEE 30 bus system is used to evaluate the algorithm that is being considered. After that, its results are compared to those of other published algorithms.

关键词： Costs Loading Valves Power electronics Power systems Fuels Optimization Load flow Intelligent control

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modeling and Design of an Autonomous Amphibious Vehicle with Obstacle Avoidance for Surveillance Applications 1

引用

1st international conference on Intelligent Computing for Sustainable Development, ICICSD 2023

作者： Jain, Dhruv Tripathi, Ganga Sagar Verma, Abhishek Department of ECE MAIT GGSIPU Delhi Delhi India Department of ECE University of Allahabad Prayaraj India Department of Information Technology Babasaheb Bhimrao Ambedkar University Uttar Pradesh Lucknow226025 India

ISBN: (数字)9783031612879

ISBN: (纸本)9783031612862

The autonomous vehicle system is built on the autopilot technique, allowing the vehicle to operate without human intervention. Equipped with sensors and actuators, the vehicle can perceive its surroundings and navigate autonomously. This promises to significantly reduce driving fatalities by replacing fallible human drivers with advanced computerized systems. With little responsibility on the driver’s part, these vehicles can travel anywhere, much like traditional cars, without requiring human assistance. The intricate system relies on sensors, actuators and complex algorithms, with each component responsible for various functions and real-time control. Such systems can revolutionize surveillance applications by providing a versatile and reliable means of transportation for monitoring operations in various terrains and environ ments. To modernize the autonomous vehicle model and make it more flexible and safe, a new system has been proposed in this paper that uses ultrasonic sensors and motor drivers for visualisation of surrounding and accordingly planning of their motion. It generally detects the obstacle by ultrasonic waves which when reflected back tell about the distance through the fed program logic. On that basis, the vehicle movement is controlled and managed in the real-time environment. The proposed autonomous vehicle system is designed to operate an amphibious vehicle, which can travel on both land and water, serving as a versatile means of transportation with obstacle avoidance regardless need of cameras on the vehicle for object detection and classification and then movement controlling. The experimental results indicate the effectiveness of the proposed system where the machine-learning algorithms are not required for effective controlling and movement of the vehicle. However, the need of efficient sensors and actuators are required for better controlling and handling for the proposed system to work efficiently in real-time environments. © The Author(s

关键词： Real time control

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11th international conference on High-Performance Computing systems and Technologies in Scientific Research, Automation of control and Production, HPCST 2021

11th International Conference on High-Performance Computing ...

引用

11th international conference on High-Performance Computing systems and Technologies in Scientific Research, Automation of control and Production, HPCST 2021

ISBN: (纸本)9783030941406

The proceedings contain 32 papers. The special focus in this conference is on High-Performance Computing systems and Technologies in Scientific Research, Automation of control and Production. The topics include: Mathematical Simulation of Coupled Elastic Deformation and Fluid Dynamics in Heterogeneous Media;numerical modeling of Electric and Magnetic Fields Induced by External Source in Frequency Domain;improving the Heterogeneous Computing Node Performance of the Desktop Grid When Searching for Orthogonal Diagonal Latin Squares;visual Metamodeling with Verification Based on Surrogate modeling for Adaptive Computing;recognition Algorithms Based on the Selection of 2D Representative Pseudo-objects;applied Interval Analysis of Big Data Using Linear Programming Methods;parallel Computing in problems of Classification of Teenagers Based on Analysis of Digital Traces;identification of Key Players in a Social Media Based on the Kendall-Wei Ranking;using Time Series and New Information Technologies for Forecasting Sugarcane Production Indicators;Calculation of Activation Functions in FPGA-Based Neuroprocessors Using the Cordic Algorithm;software and Methodology for the Design of System Dynamics Models Based on the Situation-Activity Approach;architecture of an Intelligent Network Pyrometer for Building Information-Measuring and Mechatronic systems;implementation of a Network-Centric Production Storage System in Distributed High-Performance Computing systems;internet of Things for Reducing Commercial Losses from Incorrect Activities of Personnel;method of Constructing the Assigned Trajectory of a Multi-link Manipulator Based on the "Programming by Demonstration" Approach;developing a Microprocessor-Based Equipment control Panel for Rifle Sports complexes;methods for Domain Adaptation of Automated systems for Aspect Annotation of Customer Review Texts;testing Methods for Blockchain Applications.

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Advances in Machine Learning-driven Quality control within ERP systems: A Comprehensive Survey

Advances in Machine Learning-driven Quality Control within E...

引用

IEEE international conference on Intelligent Computing and Information systems (ICICIS)

作者： Shaymaa Ahmed Qaddoori Aldoori Mohamed Mabrouk Abeer M. Mahmoud Cairo Computer Science Department Faculty of Computer and Information Science Cairo Egypt

Enterprise Resource Planning (ERP) systems have become essential instruments in contemporary corporate operations, offering significant benefits in process optimization and efficient data management. The assurance of quality and dependability in these intricate systems is of utmost significance given that errors or inconsistencies might yield extensive ramifications. This study highlights the importance of quality control within ERP systems, emphasizing the crucial role of accuracy and integrity in facilitating efficient decision-making processes and optimizing operational efficiency. This analysis explores the increasing importance of upholding ERP quality as firms become increasingly dependent on these systems to traverse intricate business environments. In addition, this study explores the capacity of machine learning to enhance quality control procedures. Machine learning techniques, owing to their ability to examine large datasets and identify subtle patterns, provide a transformative shift away from the traditional rule-based approaches. Machine learning enhances the capacity to anticipate problems, reduce interruptions, and maintain consistent operational performance by employing real-time anomaly detection, predictive modeling, and adaptation to shifting ERP settings. This study explores the complex confluence of technology and business imperatives, highlighting the transformative impact of the collaboration between machine learning and quality control on the evolution of ERP systems.

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Analysis of the Electromagnetic Field on Cable systems with Insulation Made of Polymer Materials

Analysis of the Electromagnetic Field on Cable Systems with ...

引用

international conference on control systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Nikolay K. Poluyanovich Alexander A. Sharykin Marina N. Dubyago Oleg V. Kachelaev Institute of Radio Engineering Systems and Control Southern Federal University Taganrog Russian Federation Institute of Nanotechnology Electronics and Instrumentation Southern Federal University Taganrog Russian Federation

When the EMF passes through various materials filling the inclusion, the absorption of wave energy by these substances is observed. Based on the simulation carried out using the COMSOL program, an EMF analysis was performed at the interface of dielectric media between spherical micro-inclusion and the main insulation. It is shown that in solid dielectrics, conductors, EMF absorption is significant. If a wave meets any conductor, then most of its energy is absorbed by it. The presence of heterogeneities (defects) in the insulation at the insulation - inhomogeneity interface causes jumps in the electric field strength ε1/ε2, ε 2 /ε3. The simulation and analysis of the electric field strength distribution in the defect region were carried out and it was found that with increasing Sdef, the amplitude of the magnetic induction surge (B) at the first boundary of the defect increases. With increasing Sdef. the depth of the induction failure (B) increases. However, while maintaining the overall picture, the values of dips with different types of filling inclusions are different: – the greatest gradient is observed when filled with water, the smallest when filled with carbon plus cross-linked polyethylene (C + XLPE). Thus, it can be a diagnostic parameter of the quality of the insulation of the PC. The results of the work are of interest in solving a complex of problems related to various aspects of electromagnetic compatibility and reliability of functioning of electric power systems.

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Synchronization Methods of Belt Conveyor Drive Drums

Synchronization Methods of Belt Conveyor Drive Drums

引用

Informatics, Electronics, and Radio Engineering (PIERE), international conference problems of

作者： Denis A. Kotin Stepan E. Sukhinin Ilya A. Ivanov Dept. of Electric Drives and Industry Automation Novosibirsk State Technical University Novisibirsk Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

The paper discusses the synchronization of the drive drums of a multi-motor conveyor belt. The start-up and operation of the conveyor with master-slave control systems in terms of torque and speed are investigated. Such a control system can be organized by built-in means of a frequency converter. As a result of mathematical modeling in the SimInTech environment, it was found that the master-slave speed system ensures synchronization of the speeds of the drive drums and maintenance of the traction factor equal to static at the nominal speed of rotation. The master-slave torque system provides less fluctuations in the traction factor during start-up and allows you to distribute the load moments between the motors. However, in order to ensure smooth operation of the conveyor, it is necessary to limit the driving torque of the slave motor when the traction factor exceeds the critical value. Therefore, in such a system, it is necessary to have a torque limitation unit implemented by means of a frequency converter or using an programmable logic controller.

关键词： Torque Motors Frequency conversion Belts control systems Main-secondary Sensor systems Sensors Synchronization Frequency control

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Computer Intelligence System Based on Interval Mathematical control Algorithm

Computer Intelligence System Based on Interval Mathematical ...

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Mechatronics, IoT and Industrial Informatics (ICMIII), international conference on

作者： Yanwu Liu Beijing Polytechnic Beijing China

ISBN: (数字)9798350386639

ISBN: (纸本)9798350386646

Computer intelligent system based on interval mathematical control algorithm is an automatic control system based on interval mathematical theory, which combines modern computer technology and intelligent control strategy. This kind of system realizes efficient and accurate modeling and control of complex systems by dealing with uncertain variable intervals. In practical applications, the interval mathematical control algorithm can effectively deal with the uncertainty caused by parameter changes, external disturbances and other factors, and ensure that the system behavior is always kept within the preset safety or performance limits. This kind of intelligent system is widely used in industrial process control, robot navigation, aerospace and other fields, which is of great significance to improve system reliability, robustness and intelligence level. This paper discusses an optimization algorithm, which uses the interval mathematical theory to construct the control system to achieve load balancing among the sub-nodes. The system combines modern computer technology and intelligent control strategy.

关键词： Uncertainty Service robots Process control control systems Robustness Safety Intelligent systems

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Forecasting Short-Term Load Profiles in Distribution Networks Using Machine Learning

Forecasting Short-Term Load Profiles in Distribution Network...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Sorokin Aleksandr Maltsev Roman Yablokov Andrey Titov Vladislav Electric Systems Department Ivanovo State Power Engeneering University (ISPU) Ivanovo Russia Electric Power Systems Automatic Control Department Ivanovo State Power Engeneering University (ISPU) Ivanovo Russia

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The article is devoted to the development of a machine learning model for forecasting short-term load profiles of various consumers at balance demarcation points in 6(10) kV distribution networks. The analysis, processing of initial data, training of the machine learning model, and interpretation of research results were carried out in the MATLAB software suite using the Statistics and Machine Learning Toolbox module. The assessment of the impact of forecasting errors on the operational regime of the electrical network was performed through automated modeling of distribution network operating modes using the real-time simulation software and hardware complex RTDS (Real-Time Digital Simulator).

关键词： Accuracy Machine learning Distribution networks Predictive models Mathematical models Software Real-time systems Steady-state Forecasting Load modeling

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