Search Results - (( yield prediction process algorithm ) OR ( java application testing algorithm ))

RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. Machine learning algorithms are capable of learning linear and nonlinear patterns in complex agro-meteorological data. …”

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

“…Genichi Taguchi. In the T-method prediction model, optimization of the model's accuracy is performed through feature selection process by utilizing an orthogonal array. …”

elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation by Mohamad, Sharliza

“…Refinery optimisation requires accurate prediction of crucial product properties and yield of desired products. …”
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Handling imbalance visualized pattern dataset for yield prediction by Megat Mohamed Noor, Megat Norulazmi, Jusoh, Shaidah

“…The prediction of the yield outcome in a non close loop manufacturing process can be achieved by visualizing the historical data pattern generated from the inspection machine, transform the data pattern and map it into machine learning algorithm for training, in order to automatically generate a prediction model without the visual interpretation needs to be done by human. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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BCLH2Pro: a novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes by Tuntiwongwat, Thanadol, Thammawiset, Sippawit, Srinophakun, Thongchai Rohitatisha, Ngamcharussrivichai, Chawalit, Sukpancharoen, Somboon

“…A methodology involving K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), Support Vector Machine (SVM), Random Forest (RF), and CatBoost (CB) algorithms was employed to predict H2 yields in the BCLpro, utilizing 10-fold cross-validation for robust model evaluation. …”
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Accurate Real-TIme Object Tracking with Linear Prediction Method by P. Y., Yeoh, Syed Abu Bakar, Syed Abdul Rahman

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Artificial neural network method modeling of microwave-assisted esterification of PFAD over mesoporous TiO2‒ZnO catalyst by Soltani, Soroush, Shojaei, Taha Roodbar, Khanian, Nasrin, Shean, Thomas Yaw Choong, Asim, Nilofar, Yue, Zhao

“…The esterification reaction conditions predicted by ANN showed to be potential for modeling and predicting FAME yield with an extremely well precision of 97.06%.…”
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A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm by Yahaya, Nor Zaiazmin

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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…In conclusion, the proposed method successfully yields better prediction accuracy as compared to conventional approaches. …”

Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA by Sajjadi, B., Davoody, M., Abdul Raman, Abdul Aziz, Ibrahim, Shaliza

“…The obtained results were then predicted by an optimized artificial neural network-genetic algorithm (ANN-GA) algorithm. …”
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Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

“…In general, most of the studies use predictive approach to estimate the process behaviour and a slave controller, usually proportional-integral-derivative (PID), is employed to control the process based on the estimated plant behaviour. …”
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Improving F-Score of the imbalance visualized pattern dataset for yield prediction robustness by Megat Mohamed Noor, Megat Norulazmi, Jusoh, Shaidah

“…In a non closed loop manufacturing process, a prediction model of the yield outcome can be achieved by visualizing the temporal historical data pattern generated from the inspection machine, discretize to visualized data patterns, and map them into machine learning algorithm.Our previous study shows that combination of under-sampling and over sampling techniques unabel wider range of data sets where SMOTE+VDM and random under-sampling produced robust classifier performance of handling better with different batches of prediction test data.In this paper, the integration of K* entropy base similarity distance function with SMOTE, CNN+Tomek Links and the introduction of SMOTE and SMaRT (Synthetic Majority Replacement Technique)combination, has improved the classifiers F-Score robustness.…”
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Bayesian optimized multilayer perceptron neural network modelling of biochar and syngas production from pyrolysis of biomass-derived wastes by Kanthasamy, R., Almatrafi, E., Ali, I., Hussain Sait, H., Zwawi, M., Abnisa, F., Choe Peng, L., Victor Ayodele, B.

“…While the five-layer neural network with an architecture of 3â��7-10â��3-1 displayed the best performance in predicting the syngas yield from the pyrolysis process as indicated by R2 of 0.999. …”
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Earthquake prediction model based on geomagnetic field data using automated machine learning by Yusof, Khairul Adib, Mashohor, Syamsiah, Abdullah, Mardina, Amiruddin, Mohd, Rahman, Abd, Abdul Hamid, Nurul Shazana, Qaedi, Kasyful, Matori, Khamirul Amin, Hayakawa, Masashi

“…From the implementation of five classification algorithms, neural network (NN) yielded the best-performing model with an accuracy of 83.29%. …”
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In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment by Man, Mei Yen, Mohd Saberi, Mohamad, Choon, Yee Wen, Mohd Arfian, Ismail

“…Metabolic and genetic engineering is important in producing the chemicals of interest as, without them, the product yields of many microorganisms are normally low. As a result, the aim of this paper is to propose a combination of the Bat algorithm and the minimization of metabolic adjustment (BATMOMA) to predict which genes to knock out in order to increase the succinate and lactate production rates in Escherichia coli (E. coli).…”
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Neural Network Modeling And Optimization For Enzymatic Hydrolysis Of Xylose From Rice Straw by Norhalim, Nur’atiqah

“…Then, the FANN model was used to predict the model performance with one hidden layer and the PSO and GA were used to predict the optimum conditions of the process. …”
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Identification and Grading of Manage Using Image Processing by Shukor, Syazwan

“…This project has developed an image processing algorithm for a systematic maturity identification of "Mangga Susu Thai Gold" mangos. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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