Search Results - (( java adaptation optimization algorithms ) OR ( knowledge activation function algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

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DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMZATION FRAMEWORK FOR INDUSTRIAL PROCESSES by GANESAN, TIMOTHY

“…The proposed framework is introduced as the 'surgery framework (SF)' since its prime functionality is to dissect the algorithm and add certain mechanisms into it. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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Semantic analysis system by using latent semantic analysis (LSA) algorithm on khutbah texts / Ammar Zuber by Zuber, Ammar

“…As nowadays, some muslims attend the Friday Prayers just to obey God instruction instead of willingly come to gain new knowledge. This is where the khutbah texts needs to have a certain level of quality and also new knowledge to ensure muslims does not go back home empty-handed. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

“…The proposed algorithm has the ability to improve cloudlet allocation to meet the objective function. …”
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Prediction of nanostructure of SnO2 properties using artificial neural networks / Khadijah Mohd Suhami ... [et al.] by Mohd Suhami, Khadijah, Inderan, Vicinisvarri, Senin, Syahrul Fithry, Lee, Hooi Ling

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Knowledge of extraction from trained neural network by using decision tree by Soleh, Ardiansyah, Mazlina, Abdul Majid, Jasni, Mohamad Zain

“…These knowledge are described within topology, using activation function and connection weight at hidden neurons and output neurons. …”
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Rule extraction from multi-layer perceptron neural network using decision tree for currency exchange rates forecasting by Soleh, Ardiansyah

“…Neural network can be used in acquiring hidden knowledge in datasets. However, knowledge acquired by neural network was presented in its topology, the weights on the connections and by the activation functions of the hidden and output nodes. …”
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Medical sign language translator in healthcare facility using yolo version 7 algorithm / Nurin Qistina Zaini by Zaini, Nurin Qistina

“…In addition, people who work worked at a front desk in healthcare institutions also have a limited knowledge on this sign language. Hence, this creates barrier for these impairment people to do communication in their daily activities, especially when dealing at the healthcare facility. …”
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IMPACT OF NUMBER OF ATTRIBUTES ON THE ACCURACY OF HUMAN MOTION CLASSIFICATION by Chan, Choon K, Girma, T. Chala*

“…The impact of the number of attributes on classification accuracy is evaluated via Bayes, Function, Lazy, Meta, Rule and Trees classifier algorithms supported by the WEKA tool. …”
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Online optimal tuning of fuzzy PID controller using grey wolf optimizer for quarter car semi-active suspension system by Liu, Yunyun, As’arry, Azizan, Ahmed, Hesham, Hairuddin, Abdul Aziz, Hassan, Mohd Khair, Zakaria, Mohd Zakimi, Yang, Shuai

“…This work is significant, to the best of the author’s knowledge there is no optimization method using GWO to online tune a Fuzzy PID controller for a semi-active suspension system. …”
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Agreement options for negotiation on material location decision of housing development by Utomo, C., Rahmawati, Y.

“…Social implications: The satisficing algorithm of the coalition will satisfy all stakeholders. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

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Decision Making Framework for Optimizing Construction Management Objectives: A review by Mohamed Elhassan, Sami Mustafa, Wan Abdullah Zawawi, Noor Amila, Ghazali, Zulkipli

“…Construction project including group of interrelated work activities constrained that by 13 knowledge areas. It is made up to achieve specific objectives. …”
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows by Zhang, Shasha, Dong, Qiming, Yasin, Megat Al Imran, Fang, Ng Chwee

“…Five functional layers are the components of the model architecture. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The extraction network is composed of rough neurons that accounts for the upper and lower approximations and embeds a membership function to replace ordinary activation functions. …”
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