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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Jose M. Bernal-de-Lázaro
Pág. 74 - 81
This article summarizes the main contributions of the PhD thesis titled: "Application of learning techniques based on kernel methods for the fault diagnosis in Industrial processes". This thesis focuses on the analysis and design of fault diagnosis syste...
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Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete, Francisco J. Ribadas-Pena and Néstor Bolaños
In the context of academic expert finding, this paper investigates and compares the performance of information retrieval (IR) and machine learning (ML) methods, including deep learning, to approach the problem of identifying academic figures who are expe...
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Chuanxiang Song, Seong-Yoon Shin and Kwang-Seong Shin
This study introduces a novel approach named the Dynamic Feedback-Driven Learning Optimization Framework (DFDLOF), aimed at personalizing educational pathways through machine learning technology. Our findings reveal that this framework significantly enha...
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Xiaorong Zhang, Yufeng Wang, Wenrui Ding, Qing Wang, Zhilan Zhang and Jun Jia
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Guoqing Dong, Weirong Li, Zhenzhen Dong, Cai Wang, Shihao Qian, Tianyang Zhang, Xueling Ma, Lu Zou, Keze Lin and Zhaoxia Liu
The developed prototype provides a more efficient and accurate solution for classifying dynagraph cards, meeting the requirements of oil field operations and enhancing economic benefits and work efficiency.
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Felipe Coelho de Abreu Pinna, Victor Takashi Hayashi, João Carlos Néto, Rosangela de Fátima Pereira Marquesone, Maísa Cristina Duarte, Rodrigo Suzuki Okada and Wilson Vicente Ruggiero
Complex and long interactions (e.g., a change of topic during a conversation) justify the use of dialog systems to develop task-oriented chatbots and intelligent virtual assistants. The development of dialog systems requires considerable effort and takes...
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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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Luis Zuloaga-Rotta, Rubén Borja-Rosales, Mirko Jerber Rodríguez Mallma, David Mauricio and Nelson Maculan
The forecasting of presidential election results (PERs) is a very complex problem due to the diversity of electoral factors and the uncertainty involved. The use of a hybrid approach composed of techniques such as machine learning (ML) and Simulation in ...
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Sotirios Kontogiannis, Myrto Konstantinidou, Vasileios Tsioukas and Christos Pikridas
In viticulture, downy mildew is one of the most common diseases that, if not adequately treated, can diminish production yield. However, the uncontrolled use of pesticides to alleviate its occurrence can pose significant risks for farmers, consumers, and...
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