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Marko Jevtic, Sa?a Mladenovic and Andrina Granic
Due to the everchanging and evergrowing nature of programming technologies, the gap between the programming industry?s needs and the educational capabilities of both formal and informal educational environments has never been wider. However, the need to ...
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Marian B. Gorzalczany and Filip Rudzinski
In this paper, we briefly present several modifications and generalizations of the concept of self-organizing neural networks?usually referred to as self-organizing maps (SOMs)?to illustrate their advantages in applications that range from high-dimension...
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Claudia Marzi
The paper focuses on what two different types of Recurrent Neural Networks, namely a recurrent Long Short-Term Memory and a recurrent variant of self-organizing memories, a Temporal Self-Organizing Map, can tell us about speakers? learning and processing...
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Rawan Ghnemat,Edward Jaser
Pág. pp. 4 - 11
Mobile usage is witnessing a booming growth attributed to advances in smartphone technologies, the extremely high penetration rate and the availability of popular mobile applications. Telecommunication markets have been injecting huge investments to fulf...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Marta Wlodarczyk-Sielicka and Jacek Lubczonek
At the present time, spatial data are often acquired using varied remote sensing sensors and systems, which produce big data sets. One significant product from these data is a digital model of geographical surfaces, including the surface of the sea floor...
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D. Criado-Ramón, L. G. B. Ruiz and M. C. Pegalajar
Pattern sequence-based models are a type of forecasting algorithm that utilizes clustering and other techniques to produce easily interpretable predictions faster than traditional machine learning models. This research focuses on their application in ene...
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?????? ?????????? ???????, ??????? ????????????? ??????????
Pág. 42 - 49
The subject matter of the study is data clustering based on the ensemble of neural networks. The goal of the work is to create a new approach to solving the tasks of clustering in data streams when information is fed observation-by-observation in online ...
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Fei Li, Bo Gao, Lun Shi, Hongtao Shen, Peng Tao, Hongxi Wang, Yehua Mao and Yiyi Zhao
With the increasing marketization of electricity, residential users are gradually participating in various businesses of power utility companies, and there are more and more interactive adjustments between load, source, and grid. However, the participati...
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Chenyang Wang, Wanlu Jiang, Xukang Yang and Shuqing Zhang
Predicting the remaining useful life (RUL) of mechanical equipment can improve production efficiency while effectively reducing the life cycle cost and failure rate. This paper proposes a method for predicting the remaining service life of equipment thro...
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Augusto Rafael Garrido-Arévalo, Luis Mauricio Agudelo-Otálora, Nelson Obregón-Neira, Victor Garrido-Arévalo, Edgar Eduardo Quiñones-Bolaños, Parisa Naraei, Mehrab Mehrvar and Ciro Fernando Bustillo-Lecompte
An assessment of the rainfall station distribution in the mountainous area of the Regional Autonomous Corporation of Cundinamarca (CAR, for its acronym in Spanish), Colombia, was conducted by applying concepts from information entropy and artificial neur...
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Sungwon Kim and Vijay P. Singh
The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an Internati...
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Alexander V. Khoperskov and Maxim V. Polyakov
This work includes a brief overview of the applications of the powerful and easy-to-perform method of microwave radiometry (MWR) for the diagnosis of various diseases. The main goal of this paper is to develop a method for diagnosing breast oncology base...
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Yuzhu Zhang and Hao Xu
This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present co...
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Aristeidis Karras, Anastasios Giannaros, Christos Karras, Leonidas Theodorakopoulos, Constantinos S. Mammassis, George A. Krimpas and Spyros Sioutas
In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data, enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive data produced by numerous connected devices. Our study introduces ...
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Ekaterini Hadjisolomou, Maria Rousou, Konstantinos Antoniadis, Lavrentios Vasiliades, Ioannis Kyriakides, Herodotos Herodotou and Michalis Michaelides
Eutrophication is a major environmental issue with many negative consequences, such as hypoxia and harmful cyanotoxin production. Monitoring coastal eutrophication is crucial, especially for island countries like the Republic of Cyprus, which are economi...
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Chaofeng Liu, He Yin, Yixin Sun, Ling Wang and Xiaodong Guo
Accurately identifying the key nodes of the road network and focusing on its management and control is an important means to improve the robustness and invulnerability of the road network. In this paper, a classification and identification method of key ...
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Hengyu Hu, Zhengwei He, Yanfang Ling, Junmin Li, Lu Sun, Bo Li, Junliang Liu and Wuyang Chen
In this paper, a calibration algorithm for forecasting the significant wave height (SWH) in nearshore areas is proposed, based on artificial neural networks. The algorithm has two features: first, it is based on SOM-BRFnn (self-organizing map?radial basi...
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David Balderas, Pedro Ponce, Diego Lopez-Bernal and Arturo Molina
Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. A...
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You-Da Jhong, Chang-Shian Chen, Hsin-Ping Lin and Shien-Tsung Chen
This study proposed a hybrid neural network model that combines a self-organizing map (SOM) and back-propagation neural networks (BPNNs) to model the rainfall-runoff process in a physically interpretable manner and to accurately forecast typhoon floods. ...
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