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Wind Power Prediction Based on Machine Learning and Deep Learning Models

computers, Materials & Continua 2023年第1期74卷 715-732页

作者： Zahraa Tarek Mahmoud Y.Shams Ahmed M.Elshewey El-Sayed M.El-kenawy Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Mohamed A.El-dosuky Faculty of Computers and Information Computer Science DepartmentMansoura UniversityMansoura35561Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt Faculty of Computers and Information Computer Science DepartmentSuez UniversitySuezEgypt 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 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 Arab East CollegesRiyadh13544Saudi Arabia

Wind power is one of the sustainable ways to generate renewable *** recent years,some countries have set renewables to meet future energy needs,with the primary goal of reducing emissions and promoting sustainable growth,primarily the use of wind and solar *** achieve the prediction of wind power generation,several deep and machine learning models are constructed in this article as base *** regression models are Deep neural network(DNN),k-nearest neighbor(KNN)regressor,long short-term memory(LSTM),averaging model,random forest(RF)regressor,bagging regressor,and gradient boosting(GB)*** addition,data cleaning and data preprocessing were performed to the *** dataset used in this study includes 4 features and 50530 *** accurately predict the wind power values,we propose in this paper a new optimization technique based on stochastic fractal search and particle swarm optimization(SFSPSO)to optimize the parameters of LSTM *** evaluation criteria were utilized to estimate the efficiency of the regression models,namely,mean absolute error(MAE),Nash Sutcliffe Efficiency(NSE),mean square error(MSE),coefficient of determination(R2),root mean squared error(RMSE).The experimental results illustrated that the proposed optimization of LSTM using SFS-PSO model achieved the best results with R2 equals 99.99%in predicting the wind power values.

关键词： Prediction of wind power data preprocessing performance evaluation

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Transformer-based spectro-temporal fusion for Sentinel-2 super-resolution

Transformer-based spectro-temporal fusion for Sentinel-2 sup...

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Bartlomiej Pogodzinski Tomasz Tarasiewicz Michal Kawulok Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

Multi-image super-resolution consists in fusing multiple images of the same scene to generate an image of higher spatial resolution. Recently, it has been demonstrated that for remotely sensed multispectral Sentine1-2 images, fusion performed in both spectral and temporal dimensions improves the reconstruction quality. However, the deep networks elaborated for this purpose are quite large and influence of the input data is difficult to interpret. In this paper, we show how to exploit transformer-based image fusion to reduce the number of trainable parameters by 30% and allow for increased interpretability with means of attention rollout. The reported experimental results performed over simulated and real-world data indicate that this does not affect the reconstruction quality, while at the same time the visualization tools may help in developing techniques for input data selection and preprocessing.

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EXPLORING THE CHALLENGES AND OPPORTUNITIES OF INTEGRATING ICT IN TVET

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2023年第3期85卷 49-64页

作者： Badawi, Salem Drăgoicea, Monica Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania

The labor market is constantly affected by global events and techno-logical advancements, leading to a need for the workforce to continuously ac-quire new skills. Technical and Vocational Education and Training (TVET) can provide such opportunities, with Information and Communication Technology (ICT) playing a crucial role in facilitating the process. However, the full potential of ICT in TVET has not been fully realized, and there is a gap in the knowledge regarding its role. To contribute to the body of knowl-edge, this study has conducted a systematic literature review using Natural Language Processing (NLP) tools, including Word Cloud and Topic model-ing. The findings have shown common themes addressing the role of ICT in creating and distributing educational material, creating collaborative and interactive learning environments, and providing personalized learning ex-periences. This study has revealed challenges related to ICT infrastructure, availability of ICT skills, and technical challenges including cyber-security and technical support. Furthermore, the study has identified a knowledge gap in understanding the role of ICT in the learning value-creation process. As a practical implication, this study highlights the need for future research in the field, to address the knowledge gap related to the role of Artificial Intelligence (AI) technologies in facilitating the value creation process in TVET. The findings have social implications for the development of TVET programs and the development of sustainable workforce, thus contributing to the achievement of the United Nations’ Sustainable Development Goals. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： computer aided instruction

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A HYBRID IDS ARCHITECTURE

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2023年第1期85卷 77-90页

作者： Chiriac, Beatrice-Nicoleta Anton, Florin-Daniel Ioniță, Anca-Daniela Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania

In the recent years, computing systems and applications are ubiquitous, the security and privacy are components which cannot be ignored anymore. Even if security is not a functional component of applications the concept of security and privacy by design is a hot topic addressed by companies activating in the IT field. Security has many layers and components, one of them is the monitoring and reporting component, and part of this are the intrusion detection systems (IDS). The paper is presenting an architecture of an open-source, modular, hybrid IDS system which is combining the advantages of both host and network IDS. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Cybersecurity

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Analysis of YouTube Video Comments with NLP Methods 16

Analysis of YouTube Video Comments with NLP Methods

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16th International Conference on electronics, computers and Artificial Intelligence, ECAI 2024

作者： Mironela, Pirnau Iustin, Priescu Mihaela, Priescu Catalina Claudiu, Pirnau Daniel, Ghiculescu Liviu 'Titu Maiorescu' University Faculty of Informatics Department of Informatics Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department Bucharest Romania

ISBN: (纸本)9798350371154

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of 'ChatGPT, AI clone, AI robot and Deep Learning.' © 2024 IEEE.

关键词： Deep learning

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Applying Touchscreen as Flight control Inceptor: Investigating the Perceived Workload of Interacting with Sidestick and Touchscreen Inceptors 25th

Applying Touchscreen as Flight Control Inceptor: Investigati...

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25th International Conference on Human-computer Interaction, HCII 2023

作者： Zhang, Jingyi Li, Wen-Chin Korek, Wojciech Tomasz Safety and Accident Investigation Centre SATM Cranfield University Cranfield United Kingdom Dynamics Simulation and Control Group SATM Cranfield University Cranfield United Kingdom Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (纸本)9783031480379

The widespread application of touchscreen technology brought a huge potential for future flight deck design with advanced human-computer interactive mode. The integrated flight displays that enable touchscreen input have been widely examined and validated in the aviation industry. The current research proposed an innovative surface control inceptor based on the touchscreen to control aircraft attitude in flight operations. Fifty-six participants were invited to a flight simulator experiment using the touchscreen and sidestick to perform landing tasks in the scenarios without turbulence and with turbulence. Participants’ heart rate variability (HRV) parameters during flight tasks were collected as biomarkers of mental workload. The two-way repeated measures ANOVA results demonstrated significant interactions of participants’ mean R-R interval (RR) and mean heart rate (HR) between inceptor and turbulence. The simple main effect analysis indicated that in the turbulence scenario, participants’ mean HR significantly decreased and mean RR increased using the touchscreen controller compared to the sidestick inceptor. Furthermore, the standard deviation of normal to normal R-R intervals (SDNN) was higher while performing landing tasks based on the touchscreen in turbulence and non-turbulence scenarios. These findings revealed significant decreases in workload during landing operations from both mental and physical aspects. The applicability of the touchscreen-based control surface inceptor in flight operations was confirmed. This provided a new vision of the advanced aircraft flight control system and future flight deck design for next-generation aviation operations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Aircraft control

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Evaluation of importance for condition attributes based on quality of decision reducts 26

Evaluation of importance for condition attributes based on q...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Stanczyk, Urszula Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Relative or decision reducts belong with mechanisms dedicated to feature selection, and they are embedded in rough set approach to data processing. Algorithms for reduct construction typically aim at dimensionality reduction aspect, searching for smallest reducts, which are considered as the most advantageous from the point of view of knowledge representation. However, classifiers build on reduced data models, based on reducts, can significantly vary in performance. Therefore, to ensure quality of predictions, other characteristics of reducts, apart from their cardinalities, need to be taken into account. The paper presents research in which estimation of reduct quality through their characteristics was reflected in calculation of the proposed weighting factors leading to attribute rankings. These rankings were next employed in the process of filtering decision rules, inferred by classic rough set approach. Constructed rule-based classifiers were applied in the stylometric domain to solve a task of authorship attribution. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022)

关键词： Rough set theory

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Using Fractal Techniques for Evaluation of Qualia in the Brain

Using Fractal Techniques for Evaluation of Qualia in the Bra...

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International Conference on control Systems and computer science (CSCS)

作者： Ionela Mirela Rîciu Radu Dobrescu Faculty of Automatic Control and Computer Science Bucharest Romania

This paper discusses various applications of fractals in neurosciences and presents a methodology for their investigation and modeling with appropriate software. It is presented how to use multifractal analysis for characterizing neural signals, with an emphasis on qualia fractality highlighted by the mechanisms proposed for its evaluation.

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On heterogeneity or sub-classes aspect in construction of stylometric input datasets 26

On heterogeneity or sub-classes aspect in construction of st...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Stanczyk, Urszula Baron, Grzegorz Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Stylometric analysis of texts relies on learning characteristic traits of writing styles for authors. Once these patterns are discovered, they can be compared to the ones present in other text samples, to recognise their authorship. This recognition can be compromised if input datasets are prepared without taking into consideration possible stratification of the input space, leading to specific grouping of datapoints, or sub-classes within distinguished classes. The paper shows research dedicated to construction of various structures of input datasets, and combinations of such structures between train and test sets. In the research the influence of different stratification forms on the performance of selected popular classification systems was observed. To minimise the number of influencing factors, a task of authorship attribution was performed as binary classification with balanced classes. Stylometric descriptors exploited belonged to lexical and syntactic group, giving frequencies of occurrence for chosen style-markers. It resulted in real-valued attributes and these values were explored without applying discretisation, in order to avoid the possible bias of this procedure on observations. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022)

关键词： Knowledge based systems

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Integration of Industrial Automation and IoT Devices on the Example of the Assembly Station with the Astorino Educational Robot 4th

Integration of Industrial Automation and IoT Devices on the ...

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4th International Conference on Intelligent Systems in Production Engineering and Maintenance, ISPEM 2023

作者： Ćwikla, Grzegorz Kalinowski, Krzysztof Kciuk, Marek Gold, Michal Waluśkiewicz, Marek Sladek, Michal Tlolka, Jaroslaw Woźnica, Robert Wlazlo, Aleksander Faculty of Mechanical Engineering Silesian University of Technology Konarskiego 18A Gliwice44-100 Poland Faculty of Electrical Engineering Silesian University of Technology Akademicka 10A Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9783031442810

The article presents an automated assembly station designed by students as part of Project Based Learning. The task of the project was to familiarize with the issues of integration of automation and control elements operating in various standards in order to implement the idea of Industry 4.0. The main elements of the station are the Astorino educational robot, gripper, servo drive and other professional elements of industrial automation and IoT systems. Raspberry PI, microcontrollers, etc. are also used. The assembly process of the product in the configuration in accordance with the user’s order is carried out at the station, quality control is carried out during the process using a vision system and various sensors. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data acquisition

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