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

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. …”

RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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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. …”

Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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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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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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Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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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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