Search Results - (( using normalization based algorithm ) OR ( parameter optimization model algorithm ))

Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K., S. Rama Rao., C. , -K, Chew

“…A constrained optimization on the objective function is performed using GA and SA, and optimal parameters are derived. …”
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OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K.S., Rama Rao, C. K., Chew

“…A constrained optimization on the objective function is performed using GA and SA, and optimal parameters are derived. …”
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Modelling of multi-robot system for search and rescue by Poy, Yi Ler

“…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Profit-based optimal generation scheduling of a microgrid by Muhamad Razali N.M., Hashim A.H.

“…The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”

PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

“…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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Utilizing self-organization systems for modeling and managing risk based on maintenance and repair in petrochemical industries by Jaderi, Fereshteh, Ibrahim, Zelina Zaiton, Nikoo, Mehdi, Nikoo, Mohammad

“…In order to evaluate the accuracy of the model, we compare it with the fuzzy model, and the results indicate that self-organizing systems optimized with the genetic algorithm have higher ability, flexibility and accuracy than the fuzzy model in predicting risk.…”
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Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

“…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The elements extracted from the confusion matrix parameters (i.e. accuracy, specificity, sensitivity, AUC, precision and f-score) are used in benchmarking the optimal performance of classification algorithms. …”
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Optimization of solenoid driver and controller for gaseous fuel high-pressure direct injector using model-based approach by Mohamad Hafidzul Rahman, Alias

“…An optimization study was conducted using Normal Boundary Intersection (NBI) algorithm in MATLAB Model-Based Calibration (MBC) Toolbox to produce an optimal injector setup. …”
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…A Lipschitz method and Leven berg Marquardt algorithm is used to determine the model order number and train the network respectively. …”
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Designing of prediction model for parameter optimization in cnc machining based on artificial neural network / Armansyah ... [et al.] by Armansyah, Puji, Muhammad Nurul, Mardhani, Muhammad Destri, Suartana, I Putu Eka, Desmawati, Ferdyanto, Kusumah, Muhammad Afiff, Yafi, Muhammad Umar, Saedon, Juri

“…These outputs were then utilized to train an ANN prediction model based on a feed-forward backpropagation (FFBP) algorithm. …”
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Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems by Desta, Zahlay Fitiwi

“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…Transformations are numerically optimized for linearity and normality of models. The three stem biomass equations adopted are namely, the Newton, Huber and Smalian’s formulae, based on the multiple regression (MR) and polynomial regression (PR) techniques. …”
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Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network by Al-Kharasani, Nori Mohammed Abdulkarem

“…For these reasons, optimizing routing configuration parameters, the cluster-based Quality of Service (QoS) and cross-layer parameters are an effective technique and widely accepted to improve routing performance. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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