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Francesco Curreri, Giacomo Fiumara and Maria Gabriella Xibilia
Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical d...
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Jie Zeng, Panayiotis C. Roussis, Ahmed Salih Mohammed, Chrysanthos Maraveas, Seyed Alireza Fatemi, Danial Jahed Armaghani and Panagiotis G. Asteris
This research examines the feasibility of hybridizing boosted Chi-Squared Automatic Interaction Detection (CHAID) with different kernels of support vector machine (SVM) techniques for the prediction of the peak particle velocity (PPV) induced by quarry b...
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Sergey Voronin and Jarmo Partanen
A forecasting methodology for prediction of both normal prices and price spikes in the day-ahead energy market is proposed. The method is based on an iterative strategy implemented as a combination of two modules separately applied for normal price and p...
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Sunny Diyaley, Pramod Shilal, Ishwer Shivakoti, Ranjan Kumar Ghadai, Kanak Kalita
Pág. 255 - 260
Wire electric discharge machining (WEDM) is a nontraditional machining process for machining conductive materials with complex and intricate shapes with a high surface finish and dimensional accuracy. The decision making for the selection of the best set...
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Thanh-Nam Tran, Van-Cuu Ho, Thoai Phu Vo, Khanh Ngo Nhu Tran and Miroslav Voznak
The requirements of low latency, low cost, less energy consumption, high flexibility, high network capacity, and high data safety are crucial challenges for future Internet of Things (IoT) wireless networks. Motivated by these challenges, this study deal...
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Isha Chauhan and Manav R. Bhatnagar
In this work, we investigate the impact of the transmit aperture selection technique to alleviate the effect of jamming on a free space optical (FSO) communication system. We consider the FSO system to suffer from a jamming signal and Gaussian noise conc...
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Guohua Fang, Yuxue Guo, Xianfeng Huang, Martine Rutten and Yu Yuan
Various regression models are currently applied to derive functional forms of operating rules for hydropower reservoirs. It is necessary to analyze and evaluate the model selecting uncertainty involved in reservoir operating rules for efficient hydropowe...
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Manish Sahajwani, Alok Jain and Radheyshyam Gamad
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Manish Sahajwani, Alok Jain and Radheyshyam Gamad
This paper presents log likelihood ratio (LLR) based relay selection scheme for a cooperative amplify and forward relaying system. To evaluate the performance of the aforementioned system model, a three state Markov chain based fading environment has bee...
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George Stamatellos and Tassos Stamatelos
In spite of the significant developments in machine learning methods employed for short-term electrical load forecasting on a Country level, the complexity and diversity of the problem points to the need for investing more research effort in the selectio...
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Zhongda Ren, Chuanjie Liu, Yafei Ou, Peng Zhang, Heshan Fan, Xiaolong Zhao, Heqin Cheng, Lizhi Teng, Ming Tang and Fengnian Zhou
Effectively simulating the variation in suspended sediment concentration (SSC) in estuaries during typhoons is significant for the water quality and ecological conditions of estuarine shoal wetlands and their adjacent coastal waters. During typhoons, SSC...
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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Yusuf Guzel, Gaetano Elia, Mohamed Rouainia and Gaetano Falcone
A key issue for the estimation of ground shaking is the proper selection of input motions at the seismic bedrock. At the same time, the effect of the input motion scaling strategy on structural response is typically studied disregarding the presence of t...
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Ehsan Nikkhah, Antonio Carlos Fernandes and Jean-David Caprace
Online monitoring of mooring system response for the FPSO platform in any operational condition is so far challenging for machine learning (ML). This paper presents a new dynamic NARX ANN model for time series of mooring tension and a static MLP model fo...
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Florian Kitzler, Helmut Wagentristl, Reinhard W. Neugschwandtner, Andreas Gronauer and Viktoria Motsch
Modern precision agriculture applications increasingly rely on stable computer vision outputs. An important computer vision task is to discriminate between soil and plant pixels, which is called plant segmentation. For this task, supervised learning tech...
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Christoph Zirngibl, Benjamin Schleich and Sandro Wartzack
Given strict emission targets and legal requirements, especially in the automotive industry, environmentally friendly and simultaneously versatile applicable production technologies are gaining importance. In this regard, the use of mechanical joining pr...
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Rivanda Putra,Indah Werdiningsih,Ira Puspitasari
Pág. 113 - 121
Abstrak? Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan metode VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) dan Technique for Order Prefer...
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Santiago Moreno-Carbonell and Eugenio F. Sánchez-Úbeda
The Linear Hinges Model (LHM) is an efficient approach to flexible and robust one-dimensional curve fitting under stringent high-noise conditions. However, it was initially designed to run in a single-core processor, accessing the whole input dataset. Th...
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Ihtisham Khalid, Vasilis Maglogiannis, Dries Naudts, Adnan Shahid and Ingrid Moerman
Cooperative communications advancements in Vehicular-to-Everything (V2X) are bolstering the autonomous driving paradigm. V2X nodes are connected through communication technology, such as a short-range communication mode (Dedicated Short Range Communicati...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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