Search Results - (( based optimization model algorithm ) OR ( data normalization design algorithm ))

Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

“…The accuracy from the selected most optimized models were 100%. The selected most optimized models were then can be used to classify between clean water and polluted water based on capacitance input.…”
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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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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal by Zainal, Mohamad Izwan

“…In this research, Cuckoo Search Spring Algorithm (CSSA) is proposed to enhance the robustness of algorithm by constructing the optimal network reconfiguration consist of reducing power losses and improve voltage profile with the various loadability factor as the constraint according to load profile, based on single and multiobjective model. …”
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Normalized Relational Storage for Extensible Markup Language (XML) Schema by Kamsuriah, Ahmad, Reduan, Samad

“…Approach: In this study we present an algorithm for generating an optimal design for XML in relational setting. …”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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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

“…It includes the calculation of model confidence intervals (CI) based on the assumption that model and measurement errors are normally distributed and independent. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

“…In order to increase the performance of NNBP, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are being hybrid with the ANN model to become Hybrid Neural Network Genetic Algorithm (HNNGA) model and Hybrid Neural Network Particle Swarm Optimization (HNNPSO) model respectively. …”
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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management by Eugine Teh, Yin Jie, Chee Soon, Chong, Rozaimi, Ghazali, Hazriq Izzuan, Jaafar, Muhamad Fadli, Ghani, Howe Cheng, Teng, Nur Farhanah, Zulkipli, Siaw Hong, Liew

“…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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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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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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Performance analysis of hybrid renewable energy systems used for rural electrification in Malaysia / Laith Mahmoud Mohammad Halabi by Laith Mahmoud, Mohammad Halabi

“…Accordingly, the results of predicting monthly global solar radiation showed a very good agreement between the predicted and measured data sets besides it demonstrated the high prediction capability of the developed hybrid models using standalone Adaptive Neuro-Fuzzy Inference System (ANFIS) and hybrid ANFIS models which include ANFIS-PSO (Particle Swarm Optimization), ANFIS-GA (Genetic Algorithm), and ANFIS-DE (Differential Evolution). …”
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Development of tool life prediction model of TiAlN coated tools during the high speed hard milling of AISI H13 steel by Amin, A. K. M. Nurul, Hafiz, A.M. Khalid, Lajis, M. A.

“…Experimental runs were designed based on the principles of central composite design (CCD) of RSM. …”
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SGM: Strategic Game Model for resisting node misbehaviour in IoT-Cloud ecosystem by Khan, Burhan Ul Islam, Anwar, Farhat, Abdul Rahman, Farah Diyana, Olanrewaju, Rashidah Funke, Goh, Khang Wen, Janin, Zuriati, Rahman, Md Arafatur

“…The initiation of the game model is carried out by identifying mobile node role followed by choosing an optimal payoff for a normal IoT node. …”
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Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes by Hossen, Md. Arif, Hasan, Md. Munirul, Ahmed, Yunus, Azrina, Abd Aziz, Nurashikin, Yaacof, Leong, Kah Hon

“…Six popular ML algorithms of regression, kernel and neural network-based models were applied to predict the gas-phase CO2 photoconversion rate. …”
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A New Model for Trojan Detection using Machine Learning Inspired by Al-Furqan Verse by Madihah Mohd Saudi, Areej Mustafa Abuzaid, Masrur Ibrahim

“…Moreover, the knowledge discovery techniques (KDD) and the data mining algorithm were used to optimize the accuracy result. …”

Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property by Jahanshiri, Ebrahim

“…Datasets of transacted terrace houses over the period 1999-2009 from Selangor, Malaysia were obtained and geocoded for analyses using cadastral and topographic maps and online mapping services. A complete data analysis was carried out on the datasets. Furthermore, various spatial, temporal and spatio-temporal neighbourhood and weighting schemes, optimization algorithms and lag and error modelling scenarios were created and tested with the data. …”
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SGM : Strategic game model for resisting node misbehaviour in IoT-cloud ecosystem by Khan, Burhan Ul Islam, Anwar, Farhat, Farah Diyana, Abdul Rahman, Olanrewaju, Rashidah Funke, Goh, Khang Wen, Zuriati, Janin, Rahman, Md Arafatur

“…The initiation of the game model is carried out by identifying mobile node role followed by choosing an optimal payoff for a normal IoT node. …”
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