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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

“…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

“…This model can be implemented with Raspberry Pi to simulate the object detection algorithm virtually. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”

Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…This research aimed to determine the optimal feeding strategy for fed-batch baker’s yeast fermentation process using the deep reinforcement learning algorithm in maximising the final production of yeast, while minimising the undesired ethanol formation. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. The propsed algorithm could be valuable aid for analyzing the fluid flow and reservoir simulation in an effective manner. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…According to the simulation results, the proposed EMA-DL algorithm was found to outperform all the other compared algorithms based on the evaluated metrics. …”
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Deep learning for face detection using matlab by Slim, Salim Adnan

“…This project report presents face detection using Convolutional Neural Network algorithm and Deep Learning combination (DCT / DL) throughout MATLAB simulation and modeling. …”
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Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN. by Audah, Kamil, Hussein, Walaa, Noordin, Nor Kamariah, Sali, Aduwati, A.Rasid, Mohd Fadlee

“…Simulation results demonstrate that the proposed framework improves power allocation, overall data rates, and Energy efficiency by around 15% compared to traditional deep neural network (DNN) algorithms, methods and strategies.…”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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A WAVELET BASED SIGNAL DENOISING AND HYDROCARBON PREDICTION ALGORITHM FOR A NEW MARINE CSEM ANTENNA DESIGN by NYAMASVISVA, TADIWA ELISHA

“…Massive data sets are collected from extensive simulations of a geological model using the CED and HED antennae. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

“…A step towards long network performance optimization is theterm use of deep reinforcement learning (DRL), which can learn the best policy via interaction with the environment. …”
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Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

“…This study investigated the feasibility and effectiveness of image-based techniques using advanced deep learning algorithms to quantify desiccation cracks in expansive soils. …”
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A pond-surface-based Biofloc-farm health-monitoring system for African catfish using deep learning methods by Nizam Nordin

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Predicting user trajectories using deep learning algorithms / Ahmad Zaki Aiman Abdul Rashid, Azita Laily Yusof and Norsuzila Ya’acob by Abdul Rashid, Ahmad Zaki Aiman, Yusof, Azita Laily, Ya’acob, Norsuzila

“…Due to this, this paper predicts user’s future trajectory from past trajectory utilizing deep learning (DL) algorithms which are Long-Short Term Memory (LSTM), BiDirectional LSTM, and Gated Recurrent Unit (GRU). …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Development Of Construction Noise Prediction Method Using Deep Learning Model by Siew, Jun Teng

“…A simple prediction chart method was developed on top of a stochastic algorithm called Monte Carlo simulation by complying with the standard BS 5228 for the noise prediction in the environmental impact assessment during the planning stage of a construction project. …”
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