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Ekaterina Koroleva
This paper aims to examine the interplay between the attributes of the FinTech ecosystem (input) and productive entrepreneurship (output) in Russian regions. A survey was used to gather data from FinTech representatives in ten selected regions located in...
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Seongwan Kim and Jongsu Kim
This paper introduces an optimal energy control method whose rule-based control employs the equivalent consumption minimization strategy as the design standard to support a neural network technique. Using the proposed control method, the output command v...
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Tameem Adel and Mark Levene
We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks. Side information can be viewed as expert knowledge, additional to the input, that may come from a knowledge base. Unlike ...
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Ana Ramos Oliveira, Tiago Brito Ramos and Ramiro Neves
This study compares the performance of three different neural network models to estimate daily streamflow in a watershed under a natural flow regime. Based on existing and public tools, different types of NN models were developed, namely, multi-layer per...
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Sergei Strijhak, Daniil Ryazanov, Konstantin Koshelev and Aleksandr Ivanov
In this article the procedure and method for the ice accretion prediction for different airfoils using artificial neural networks (ANNs) are discussed. A dataset for the neural network is based on the numerical experiment results?obtained through iceFoam...
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Ramachandran Manickam
Pág. 203 - 208
The present study has used an ANN to predict shell molding performances ? permeability number and transverse strength- of sand moulds employed in hot metal casting. A back propagation ANN is used. This study utilized actual experimental data in which inp...
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Aleksandra Banasiewicz, Forougholsadat Moosavi, Michalina Kotyla, Pawel Sliwinski, Pavlo Krot, Jacek Wodecki and Radoslaw Zimroz
An approach based on an artificial neural network (ANN) for the prediction of NOx emissions from underground load?haul?dumping (LHD) vehicles powered by diesel engines is proposed. A Feed-Forward Neural Network, the Multi-Layer Perceptron (MLP), is used ...
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Xin-Yi Yuan, Yue Hua, Nadine Aubry, Mansur Zhussupbekov, James F. Antaki, Zhi-Fu Zhou and Jiang-Zhou Peng
This study develops a data-driven reduced-order model based on a deep convolutional neural network (CNN) for real-time and accurate prediction of the drug trajectory and concentration field in transarterial chemoembolization therapy to assist in directin...
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Dan Zhang, Yinghong Wen, Jinbao Zhang, Jianjun Xiao, Yali Song and Qi Geng
For high-speed train, balise transmission module (BTM) system is easily interfered with by other equipment of the train. This could cause the train to malfunction. Studying the electromagnetic susceptibility (EMS) of the BTM is very important for the per...
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Azzad Bader SAEED
Pág. 395 - 411
In this paper, an artificial intelligent system has been designed, realized, and downloaded into FPGA (Field Programmable Gate Array), which is used to control five speed ratio steps ( 1,2,3,4,5) of an electrically controlled type of ...
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Ceyhun Karpuz, Mehmet Cakir, Ali Kursad Gorur and Adnan Gorur
In this paper, new single/double-layer N-way Wilkinson power dividers (WPDs) were designed by using slow-wave structures such as narrow-slit-loaded and meandered transmission lines. For size reduction, the slit-loaded and meandered lines were used instea...
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Accurate short-term electric load forecasting is significant for the smart grid. It can reduce electric power consumption and ensure the balance between power supply and demand. In this paper, the Stacked Denoising Auto-Encoder (SDAE) is adopted for shor...
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Jin Woo Moon, Min Hee Chung, Hayub Song and Se-Young Lee
The aim of this study was to develop an artificial neural network (ANN) prediction model for controlling building heating systems. This model was used to calculate the ascent time of indoor temperature from the setback period (when a building was not occ...
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Xiuying Xu, Changhao Fu, Yingying Gao, Ye Kang and Wei Zhang
The origin of seeds is a crucial environmental factor that significantly impacts crop production. Accurate identification of seed origin holds immense importance for ensuring traceability in the seed industry. Currently, traditional methods used for iden...
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Sultan Ahmed Almalki, Ahmed Abdel-Rahim and Frederick T. Sheldon
The adoption of cooperative intelligent transportation systems (cITSs) improves road safety and traffic efficiency. Vehicles connected to cITS form vehicular ad hoc networks (VANET) to exchange messages. Like other networks and systems, cITSs are targete...
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Jianwu Lin, Xiaoyulong Chen, Renyong Pan, Tengbao Cao, Jitong Cai, Yang Chen, Xishun Peng, Tomislav Cernava and Xin Zhang
Most convolutional neural network (CNN) models have various difficulties in identifying crop diseases owing to morphological and physiological changes in crop tissues, and cells. Furthermore, a single crop disease can show different symptoms. Usually, th...
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Edvaldo Domingos, Blessing Ojeme and Olawande Daramola
Until recently, traditional machine learning techniques (TMLTs) such as multilayer perceptrons (MLPs) and support vector machines (SVMs) have been used successfully for churn prediction, but with significant efforts expended on the configuration of the t...
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Yanyan Kang, Wanting Lv, Jinyan He and Xianrong Ding
Measurement of beach heights in the intertidal zone has great importance for dynamic geomorphology research, coastal zone management, and the protection of ecological resources. Based on satellite images, the waterline method based on satellite images is...
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Do-Soo Kwon, Chungkuk Jin, MooHyun Kim and Weoncheol Koo
This paper presents a machine learning method for detecting the mooring failures of SFT (submerged floating tunnel) based on DNN (deep neural network). The floater-mooring-coupled hydro-elastic time-domain numerical simulations are conducted under variou...
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Budiman Putra Asma'ur Rohman, Catur Hilman, Erik Tridianto, Teguh Hady Ariwibowo
Pág. 275 - 288
Solar power is a renewable energy interest many researchers around the world to be explored for human life beneficial especially for electric power generation. Photovoltaic (PV) is one of technology developed massively to exploit the solar power for this...
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