Results 11 to 20 of about 984,534 (293)
Environmental Research Communications, 2023 The paper proposes a prediction algorithm that is composed with principal component analysis (PCA), grid search (GS) and K-nearest neighbours (KNN). Firstly, in order to solve the problem of multicollinearity in multiple regression, principal component ...
Yanwei Qi +3 more
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Journal of Applied Informatics and Computing, 2023 Classification is one of the important tasks in the field of Machine Learning. Classification can be viewed as an Optimization Problem (Optimization Problem) with the aim of finding the best model that can represent the relationship/pattern between data ...
Muhamad Fajri, Aji Primajaya
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Grid Search of Convolutional Neural Network model in the case of load forecasting [PDF]
Archives of Electrical Engineering, 2021 The Convolutional Neural Network (CNN) model is one of the most effective models for load forecasting with hyperparameters which can be used not only to determine the CNN structure and but also to train the CNN model.
Thanh Ngoc Tran
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Perbandingan Kinerja Algoritma Optimasi pada Metode Random Forest untuk Deteksi Kegagalan Jantung
Jurnal Rekayasa Elektrika, 2022 Abstrak— Jantung merupakan salah satu organ terpenting dalam tubuh manusia. Kegagalan jantung pada pasien dapat mengakibatkan dampak yang vital dan berujung pada kematian.
Unang Sunarya, Tita Haryanti
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IEEE Access, 2020 Swirl-based inline phase separation is a promising approach in the process industry with potential application in oil and gas separation in petroleum industry. To increase the efficiency of the separation, the process may be controlled. In this direction,
Muhammad Awais Sattar +6 more
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Prediction Model for Transient NOx Emission of Diesel Engine Based on CNN-LSTM Network
Energies, 2023 In order to address the challenge of accurately predicting nitrogen oxide (NOx) emission from diesel engines in transient operation using traditional neural network models, this study proposes a NOx emission forecasting model based on a hybrid neural ...
Qianqiao Shen +5 more
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Spatial search on grids with minimum memory [PDF]
Quantum Information and Computation, 2015 We study quantum algorithms for spatial search on finite dimensional grids. Patel \textit{et al.}~and Falk have proposed algorithms based on a quantum walk without a coin, with different operators applied at even and odd steps. Until now, such algorithms have been studied only using numerical simulations.
Ambainis, Andris +2 more
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From access and integration to mining of secure genomic data sets across the grid [PDF]
, 2007 The UK Department of Trade and Industry (DTI) funded BRIDGES project (Biomedical Research Informatics Delivered by Grid Enabled Services) has developed a Grid infrastructure to support cardiovascular research.
Sinnott, R.O.
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Deep Learning Optimisation of Static Malware Detection with Grid Search and Covering Arrays
Telecom, 2023 This paper investigates the impact of several hyperparameters on static malware detection using deep learning, including the number of epochs, batch size, number of layers and neurons, optimisation method, dropout rate, type of activation function, and ...
Fahad T. ALGorain +1 more
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BIBC Matrix Modification for Network Topology Changes: Reconfiguration Problem Implementation
Energies, 2021 The topology of a distribution network can be represented by a bus injection to branch current (BIBC) matrix. It has been introduced and used for load flow analysis of distribution networks.
Ayşe Aybike Şeker +2 more
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