Search Results - (( developing fraction learning algorithm ) OR ( java optimization modified algorithm ))

OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

“…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

“…The recent development of knowledge in fractional calculus introduced an advanced superior operator known as fractal–fractional derivative (FFD). …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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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

“…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato... by Alsa’Di, Kawthar, Nik Long, Nik Mohd Asri

“…Moreover, a new hybrid technique which is the combination of deep learning artificial neural network and finite difference method (FDL-ANN) is developed to approximate the solution of higher order VFIDEs. …”
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Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions by Alsa’di, Kawthar, Nik Long, Nik Mohd Asri, Senu, Norazak, Eshkuvatov, Z.K.

“…A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
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Predictive modelling of nanofluids thermophysical properties using machine learning by Olanrewaju, Alade Ibrahim

“…This thesis aimed to develop machine learning algorithms to estimate the thermophysical properties of commonly used nanofluids. …”
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Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

“…In the second part of the thesis, we developed the Hilfer fractal-fractional derivative definition. …”
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An improved vulnerability exploitation prediction model with novel cost function and custom trained word vector embedding by Hoque M.S., Jamil N., Amin N., Lam K.-Y.

Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

“…The resultant semantic maps are inserted into the decoder fraction to obtain the full-resolution probability maps. …”

Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine by Jahirul, M.I., Saidur, Rahman, Masjuki, Haji Hassan

“…The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. …”
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

“…Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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Parametric investigation of battery thermal management system with phase change material, metal foam, and fins; utilizing CFD and ANN models by Najafi Khaboshan, Hasan, Jaliliantabar, Farzad, Abdul Adam, Abdullah, Panchal, Satyam, Azarinia, Amiratabak

“…Finally, an artificial neural network model is developed using the backpropagation learning technique coupled with the gradient descent optimization algorithm. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz by Abd Aziz, Nur Hasyimah

“…Next, the system was successfully developed by implementing the best CNN model as a classifier. …”
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization by Nader Ibrahim Namazi, Sameer Alshehri, Rawan Bafail, Bader Huwaimel, Amal M. Alsubaiyel, Ali H. Alamri, Ahmed D. Alatawi, Hossam Kotb, Mohd Sani Sarjadi, Md. Lutfor Rahman, Mohammed A.S. Abourehab

“…Finally, the optimal values are (P = 400 bar, T = 3.38 K 102, Y = 1.064 10ˉ³ mol fraction) using this model.…”
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