Search Results - (( using function method algorithm ) OR ( yield prediction method algorithm ))

Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

“…Based on the experimental results, the proposed feature selection method successfully found a superior combination that yields a better result in terms of the objective function. …”

Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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A framework for predicting oil-palm yield from climate data by Awan, A. Majid, Md. Sap, Mohd. Noor

“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.…”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

“…As a result, improved multivariable genetic algorithm (IMGA) with adaptable fitness function ability is introduced in this work. …”
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Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment by Tang, Phooi Wah, Choon, Yee Wen, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi

“…Using numeral optimisation algorithms to identify gene knockouts may stall at a local minimum in a multivariable function. …”
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Comparison of CPU damage prediction accuracy between certainty factor and forward chaining techniques by Tri Ginanjar Laksana, Ade Rahmat Iskandar, Wan Nooraishya Wan Ahmad

“…The suggested algorithm yields the mean accuracy of the certainty factor approach in diagnosing computer damage utilizing the constructed system. …”
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SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

“…Data-driven models for predicting fire and explosion-related properties have been improved greatly in recent years using machine-learning algorithms. …”
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Optimization of coded signals based on wavelet neural network by Ahmed, Mustafa Sami

“…When compared with other existing methods, WNN yields better PSR, low Mean Square Error (MSE), less noise, range resolution ability and Doppler shift performance than the previous and some traditional algorithms like auto correlation function (ACF) algorithm.…”
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Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

“…Metaheuristic optimization algorithms are well-established techniques to address those problems which are difficult to solve through traditional optimization methods. …”
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Enhancement of Ethanol Production Using a Hybrid of Firefly Algorithm and Dynamic Flux Balance Analysis by Wan, Ting Leong, Mohd Saberi, Mohamad, Kohbalan, Moorthy, Yee, Wen Choon, Hasyiya Karimah, Adli, Khairul Nizar Syazwan, W. S. W, Loo, Keat Wei, Nazar, Zaki

“…To predict the gene knockout list that can generate high yields of desired product, a hybrid of firefly algorithm and dynamic flux balance analysis (FADFBA) is proposed. …”
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Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

“…Real yield data which was obtained from Fuji Electric Malaysia has been used in this research. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Prediction of fruit ripening by Artificial Neural Network based on relationship between pectin and image analysis / Aisyah Sakina Shahrin ... [et al.] by Shahrin, Aisyah Sakina, Osman, Mohamed Syazwan, Ramli, Rafidah Aida, Setumin, Samsul, Senin, Syahrul Fitry

“…Thus, the solution to those limitations is Artificial Neural Network (ANN). The models used is MLP model with back-propagation algorithms with the help of learning function of Bayesian regularization and the transfer function is tangent hyperbolic. …”
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Experimental Analysis on Parameters Affecting the Material Removal Rate in Wire Electrical Discharge Turning using the Taguchi Method by Saiful Bahri, Mohamed

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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

“…Using a production related heuristic method which is called system value method, the value of each workstation is determined. …”
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An improved artificial neural network based model for prediction of late onset heart failure by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…The MLP model was used to optimize the predicting algorithm based on the conjugate gradients descent method. …”
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Development of finite element model for soil-structure interaction by Shoaei, Mohammad Dalili

“…Comparisons showed acceptable accuracy and reasonable prediction of the analysis. Results from ANN showed good agreement with the classical method. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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Process intensification of hydrogen production by catalytic steam methane reforming: Performance analysis of multilayer perceptron-artificial neural networks and nonlinear response... by Ayodele B.V., Alsaffar M.A., Mustapa S.I., Adesina A., Kanthasamy R., Witoon T., Abdullah S.