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2022 Conference of Russian Young Researchers in Electrical and Electronic engineering, ElConRus 2022

作者： Krutikov, Alexander K. Meltsov, Vasily Y. Strabykin, Dmitry A. Vyatka State University Faculty of Automation and Computer Engineering Department of Electronic Computers Kirov Russia

ISBN: (纸本)9781665409933

Well-known implementations of software systems for predicting sports events based on artificial neural networks do not provide sufficiently accurate results in individual sports. The main difficulty in this case is the fact that various types and formats of data act as source information: numeric, symbolic, interval. The authors propose an approach based on cascading of several types of neural networks. A specialized training sample is prepared for each module in accordance with the type of model and the selected cascade structure. The results of information processing on each layer serve as data sets for modules of subsequent tiers. Initially, the system was implemented using the MATLAB package. The experiments carried out confirm the effectiveness of cascading modules. To significantly increase the performance of the system, for example, when used in betting shops, a cascade of neural networks is implemented on the basis of Altera Cyclone III FPGA using Quartus CAD. © 2022 IEEE.

关键词： Neural networks

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Relative Flash LiDAR Aided-Inertial Navigation using Surfel Grid Maps

Relative Flash LiDAR Aided-Inertial Navigation using Surfel ...

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2022 IEEE Aerospace Conference, AERO 2022

作者： Liu, Bangshang Sazdovski, Vasko Janschek, Klaus Institute of Automation Technische Universitaet Dresden Faculty of Electrical and Computer Engineering Dresden01062 Germany

ISBN: (数字)9781665437608

ISBN: (纸本)9781665437608

This paper proposes a relative navigation framework using flash LiDAR aided-inertial navigation and surfel grid maps for in-situ autonomous exploration of small solar system bodies' (SSSB) surfaces. The key idea of the relative navigation is division of an entire flight area into several sub-areas, in each of which local navigation estimates and a local map are created in a node frame representing local frame in that sub-area. By changing the node frame in different sub-areas, estimation error and mapping error are bounded and do not accumulate. Varying local gravity vector on the SSSB surface is taken into account when a new node frame is defined. Our flash LiDAR pre-processing applies a scan-to-map matching algorithm and provides direct observation of spacecraft's position and attitude in the node frame to an error state Kalman filter. The surfel grid map representing local terrestrial environment around the spacecraft permits efficient scan-to-map matching and straightforward analysis on the SSSB surface. Simulation tests in a specialized high fidelity simulated SSSB environment present results of validation and performance evaluation of our relative navigation solution and show the viability of this novel navigation solution. © 2022 IEEE.

关键词： Errors

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Accelerated Algorithm for Counting the Amount of Numbers in Specified Ranges

Accelerated Algorithm for Counting the Amount of Numbers in ...

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2022 Conference of Russian Young Researchers in Electrical and Electronic engineering, ElConRus 2022

作者： Krutikov, Alexander K. Strabykin, Dmitry A. Lapitsky, Alexey A. Vyatka State University Faculty of Automation and Computer Engineering Department of Electronic Computers Kirov Russia

ISBN: (纸本)9781665409933

An accelerated algorithm for calculating the number of array numbers that fit in each of the specified ranges is proposed. The algorithm assumes that the number of ranges is a multiple of the power of two, the bit depth of the maximum number of the array does not exceed the bit depth of the memory cell used to store it. The acceleration of counting numbers is based on the conversion of the analyzed number of the source array to the address of the memory cell corresponding to the range of the number. This conversion reduces the time for counting the number of numbers in the source array that fit into the specified ranges by eliminating memory accesses to read the boundary values of the addresses of the ranges. The time estimates of the algorithm execution are given, the prospects of using the algorithm in solving problems are noted. © 2022 IEEE.

关键词： Array processing

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A New Fuzzy Adaptive Algorithm to Classify Imbalanced Data

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computers, Materials & Continua 2022年第1期70卷 73-89页

作者： Harshita Patel Dharmendra Singh Rajput Ovidiu Petru Stan Liviu Cristian Miclea School of Information Technology&Engineering Vellore Institute of TechnologyVellore632014India Technical University of Cluj Napoca Faculty of Automation and Computer ScienceCluj Napoca400114Romania

Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other *** Imbalanced distribution of data is a natural occurrence in real world datasets,so needed to be dealt with carefully to get important *** case of imbalance in data sets,traditional classifiers have to sacrifice their performances,therefore lead to *** paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this *** have adapted the‘existing algorithm modification solution’to learn from imbalanced datasets that classify data without manipulating the natural distribution of data unlike the other popular data balancing *** K nearest neighbor is a non-parametric classification method that is mostly used in machine learning *** classification with the nearest neighbor clears the belonging of an instance to classes and optimal weights with improved nearest neighbor concept helping to correctly classify imbalanced *** proposed hybrid approach takes care of imbalance nature of data and reduces the inaccuracies appear in applications of original and traditional *** show that it performs well over the existing fuzzy nearest neighbor and weighted neighbor strategies for imbalanced learning.

关键词： Machine learning fuzzy classification nearest neighbor adaptive approach optimal weights

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Target tracking method of Siamese networks based on the broad learning system

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1043-1057页

作者： Dan Zhang C.L.Philip Chen Tieshan Li Yi Zuo Nguyen Quang Duy Navigation College Dalian Maritime UniversityDalianChina Innovation and Entrepreneurship Education College Dalian Minzu UniversityDalianChina Computer Science and Engineering College South China University of TechnologyGuangzhouChina Department of Computer and Information Science Faculty of Science and TechnologyUniversity of MacaoMacaoChina School of Automation Engineering University of Electronic Science and Technology of ChinaChengduChina Faculty of Navigation Vietnam Maritime UniversityHaiphongVietnam

Target tracking has a wide range of applications in intelligent transportation,real‐time monitoring,human‐computer interaction and other ***,in the tracking process,the target is prone to deformation,occlusion,loss,scale variation,background clutter,illumination variation,etc.,which bring great challenges to realize accurate and real‐time *** based on Siamese networks promotes the application of deep learning in the field of target tracking,ensuring both accuracy and real‐time ***,due to its offline training,it is difficult to deal with the fast motion,serious occlusion,loss and deformation of the target during ***,it is very helpful to improve the performance of the Siamese networks by learning new features of the target quickly and updating the target position in time *** broad learning system(BLS)has a simple network structure,high learning efficiency,and strong feature learning *** at the problems of Siamese networks and the characteristics of BLS,a target tracking method based on BLS is *** method combines offline training with fast online learning of new features,which not only adopts the powerful feature representation ability of deep learning,but also skillfully uses the BLS for re‐learning and re‐*** broad re‐learning information is used for re‐detection when the target tracking appears serious occlusion and so on,so as to change the selection of the Siamese networks search area,solve the problem that the search range cannot meet the fast motion of the target,and improve the *** results show that the proposed method achieves good results on three challenging datasets and improves the performance of the basic algorithm in difficult scenarios.

关键词： broad learning system siamese network target tracking

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On Efficient Planning of Oil&Gas Investments and Characteristics of BMS-models Destabilization 16

On Efficient Planning of Oil&Gas Investments and Characteris...

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

作者： Zholkov Jolkov, Sergei Shashev, A.M. National University of Oil and Gas 'Gubkin University' Faculty of Automation and Computer Engineering Moscow Russia Moscow Institute of Physics and Technology Department of Radio Engineering and Cybernetics Moscow Russia

ISBN: (纸本)9798350337907

With an unconventional approach, we regard the problem of building a precise adaptive model of oil price dynamics in the context of investment projects. I. Newton formulated the principle of analysis. We list the Principles of applying the stochastic theory of asset management to building the optimal investment projects in oil and gas field development. We also analyze all the data of daily oil exchange from 1988 to 2019 (spot prices, Platts (Platt's) McGraw Hill Financial). We use methods and quantitative evaluations of adaptive BMS models with stochastic switches. We outline precise (normalized quadratic deviation within 9%) adaptive BMS models, plot extrapolation (quasi-forecast) on a stability period;make a stability period quasi-forecast and list essential quantitative evaluations and graphs. We discuss the possibility of quick profiting using BMS models. We also discuss the approaches to solving the problem of building optimal midterm oil and gas field development projects and operations, as well as the results we acquire. Analysis of incomes and expenses of an optimal investment project would allow for a substantiated decision on whether the development should be started or forgone. © 2023 IEEE.

关键词： Random processes

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Drone-Based Predictive Structure Analysis: A Review

Drone-Based Predictive Structure Analysis: A Review

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Patil, Trushant Nandan, Durgesh Sharma, Kanhaiya Parashar, Deepak Department of Robotics and Automation Pune India Department of Electronics and Telecommunication Engg. Pune India Department of Computer Science & Engineering Pune India Faculty of Engineering Pune India

ISBN: (纸本)9798350329186

Drone-based predictive structure analysis is a rapidly growing field that has the potential to revolutionize infrastructure and building inspection. In this review of the research, we give a general overview of how drones could increase the effectiveness and precision of structural analysis, particularly for keeping an eye on difficult-to-reach locations. The usage of drones for 3D mapping, inspection, and monitoring of diverse constructions, such as concrete buildings, bridges, tunnels, and dams. The investigations show that drone-based inspection can produce 3D models and high-resolution photos, allowing for remote monitoring and the early identification of possible problems. The findings show that drones may greatly boost infrastructure management's safety and effectiveness, making them an important tool for predictive structural research. © 2023 IEEE.

关键词： Drones

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A New Technique of Soluble NPK Nutrient Detection System Using Deep Learning-Based Recurrent Neural Networks (RNN) 12

A New Technique of Soluble NPK Nutrient Detection System Usi...

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12th International Electrical engineering Congress, iEECON 2024

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University Of Technology Krungthep Department Of Electrical And Telecommunication Engineering Bangkok Thailand Thammasat School Of Engineering Thammasat University Faculty Of Engineering Department Of Electrical And Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department Of Robotic Engineering And Automation System Bangkok Thailand

ISBN: (纸本)9798350383591

Modern agriculture relies heavily on effective process monitoring, control, and remote data collection, making accurate and cost-effective sensors crucial for innovation. This research focuses on the development of a spectroscopy-based device for real-time and remote monitoring of nutrient levels in hydroponic systems. The device utilizes IoT architecture, incorporating principles of light absorbance to quantify concentrations of essential nutrients during crop growth. Three deep learning techniques, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) were adopted for data analysis. Results demonstrate that tailored implementation of deep learning can significantly enhance the performance of sensor network system (SNS). Specifically, the RNN format achieved an impressive 98% model accuracy during both training and testing phases. The technological advancements in addressing contract variation and photometric levels contribute to increased accuracy as more sensors become available. The findings serve as a comprehensive guide for collecting extensive agricultural data, encompassing environmental factors throughout the entire cultivation period, using state-of-the-art remote control sensor equipment. This work provides a practical, efficient, and cost-effective solution for precise nutrient control and continuous data monitoring in agricultural production. © 2024 IEEE.

关键词： Cost effectiveness

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Resonant PI Controller Design for the Electrohydraulic Drive of a Stabilized Platform System 24

Resonant PI Controller Design for the Electrohydraulic Drive...

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24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Van Tam, Bui Yurkevich, Valery D. Novosibisk State Technical University Faculty of Automation and Computer Engineering Novosibisk Russia Novosibirsk State University Novosibisk State Technical University Novosibisk Russia

ISBN: (纸本)9798350336870

The problem of stabilizing the position of a platform installed on the deck of a ship is considered. The platform is used to accommodate navigation equipment and antennas for radar communication systems. The system of stabilized platforms improves the working conditions of such special equipment by suppressing wave disturbances in the aquatic environment. This article discusses the methodology for designing an electro-hydraulic drive controller that ensures the angular stability of a stabilized platform under the influence of wave interference. Elimination of the influence of wave disturbances on the angle of deviation of the platform from the horizon is the control objective. The article considers a mathematical model of a stabilized platform with an electro-hydraulic drive and proposes a method for designing a control system that effectively suppresses the influence of wave disturbances on the angular position of the platform. Innovative in the proposed approach to building a position control system for a stabilized platform is the implementation of the time-scale separation method for calculating the resonant proportional-integral controller of an electro-hydraulic drive platform. The proposed method for constructing the controller allows for effective suppression of the effect of harmonic interference with a known frequency but an unknown amplitude. The results of the numerical simulation of the considered control system are presented. © 2023 IEEE.

关键词： Controllers

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Advanced Analysis of Electro-Oculographic Signal using Deep Neural Networks for Safety Purposes in automation and Production Systems 15

Advanced Analysis of Electro-Oculographic Signal using Deep ...

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15th International Conference on computer and automation engineering, ICCAE 2023

作者： Kuric, Ivan Stenchlak, Vladimir Zajacko, Ivan Bohusik, Martin Wiecek, Dorota University of Žilina Department of Automation and Production Systems Žilina Slovakia University of Bielsko-Biala Faculty of Mechanical Engineering and Computer Science Bielsko-Biala Poland

ISBN: (纸本)9798350396225

This article deals with the problematics of obtaining and processing the EOG signals. This research describes the ways in which it is possible to measure and evaluate the measured bio-electrical signals of brain and muscle activity in more detail. The work also describes the analysis of the current state of this problematics and individual models of artificial intelligence are also described in the work - artificial neural networks that can be used for such advanced analysis. The experimental part of this work is performed in the MATLAB environment using the Deep Neural Network Toolbox. The experimental part of the work is focused on the analysis and processing of bio-electrical activity eye-motor muscles in the area of eye-tracking with the help of the OLIMEX EEG-SMT device. The information provided in this research can be used for improving safety and reliability and elimination of potential risks connected to an epilepsy disease and epilepsy seizures in automated production systems. © 2023 IEEE.

关键词： Deep neural networks

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