Search Results - (( using function based algorithm ) OR ( using composition learning algorithm ))

Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. …”
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A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

“…This study presents a novel softsign-function-based fractional-order proportional–integral–derivative (softsign-FOPID) controller optimized using the fungal growth optimizer (FGO) for the stabilization and precise position control of an unstable magnetic ball suspension system. …”
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Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

“…In this thesis, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as one recent and composite architecture of reinforcement learning (RL), has been explored as a tracking agent for the problem of UAV-based target tracking. …”
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Simultaneous fault diagnosis based on multiple kernel support vector machine in nonlinear dynamic distillation column by Taqvi, S.A.A., Zabiri, H., Uddin, F., Naqvi, M., Tufa, L.D., Kazmi, M., Rubab, S., Naqvi, S.R., Maulud, A.S.

“…In the developed MK-SVM algorithm, multilabel approach based on various kernel functions has been utilized for the classification of simultaneous faults. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…The combination of these two aspects can assist to balance and enhance the exploration and exploitation capability. Before using the JAABC5ROC as an optimizer for the SVM, a total of 10 benchmark function were used to determine its performance assessment 5 common benchmarks which are (Shows Rosenbrok, Sphere, Step and RS Schwefel Ridges and RS Zekhelip) and 5 CEC2017 benchmarks which are (Shifted and Rotated Zakharov Function, Hybrid Function 01, Composite Function 08, Composite Function 09 and Composite Function 10). …”
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater by Ghumman, A.S.M., Shamsuddin, R., Abbasi, A., Ahmad, M., Yoshida, Y., Sami, A., Almohamadi, H.

“…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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Twin delayed deep deterministic policy gradient-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage training by Abo Mosali, Najmaddin, Shamsudin, Syariful Syafiq, Alfandi, Omar, Omar, Rosli, AL-Fadhali, Najib

“…In this article, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as recent and composite architecture of RL, was explored as a tracking agent for the UAV-based target tracking problem. …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Computational analysis of biological data: Where are we? by Soreq, Lilach, Mohamed, Wael Mohamed Yousef

“…Computer modeling allows such electrical stimulations using statistics, bioinformatics and advanced machine-learning algorithms. …”
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Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network by Langroodi, Naz Chaibakhsh

“…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of seven hidden nodes with hyperbolic tangent sigmoid transfer function. …”
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms by Shaikh, Abdul Aabid, Raheman, Md Abdul, Hrairi, Meftah, Baig, Muneer

“…On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. …”
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Analysis of photovoltaic panels performance and power output forecasting based on optimized deep learning technique / Muhammad Naveed Akhter by Muhammad Naveed, Akhter

“…Moreover, Salp Swarm Algorithm (SSA) is used to tune the hyperparameters of the developed deep learning method on an annual basis over four years to enhance its forecasting accuracy and is compared with RNN-LSTM, GA-RNN-LSTM, and PSO-RNN-LSTM. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission by Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.

“…This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. …”
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A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

“…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources by Al-Qadhi, Abdulrahman K., Athauda, Rukshan, Latip, Rohaya, Hussin, Masnida

“…To initialise function placement, Fitness-Based Swap (FBSW) algorithm is proposed which places functions based on pre-defined information such as function size, function maximum execution time, and storage cost. …”
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Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

“…In comparison to the other widely used conventional learning algorithms, the ELM has a much faster learning ability.…”
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A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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Computation of cryptosystem based on Lucas functions using addition chain by Md Ali, Zulkarnain, Othman, Mohamed, Md. Said, Mohamad Rushdan, Sulaiman, Md. Nasir

“…Cryptosystem based on Lucas Functions is known as LUC Cryptosystem. …”
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An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation by Ismael, Ahmed Naser

“…Hence, this study proposes an Improved Fast Scanning algorithm that is based on Sorensen distance measure and adaptive threshold function. …”
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