Search Results - (( rice processing based algorithm ) OR ( java application path algorithm ))

Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming by Zun Liang, Chuan, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, David Lau, King Luen, Chong, Yeh Sai

“…To address these challenges, an innovative Artificial Intelligence-based (AI-based) predictive algorithm has been proposed, leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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Monitoring the drying process of glutinous rice using hyperspectral imaging coupled with multivariate analysis by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah

“…The model prediction performance shows an accuracy (R²P) of 0.9206 with RMSEP of 1.1410. Using CARS algorithm resulted in the selection of 21 optimal wavelengths that are highly associated with the moisture content of glutinous rice during the drying process and the developed PLS model based on the selected wavelength gave an increased model accuracy with R2CV and RMSECV of 0.9176 and 1.0986 respectively. …”
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Smart agriculture economics and engineering: Unveiling the innovation behind ai-enhanced rice farming by Chuan, Zun Liang, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, Chong, Yeh Sai

“…This article introduced innovative Artificial Intelligence-based (AI-based) predictive algorithms for short-term rice production, utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks by Rayner Alfred, Joe Henry Obit, Christie Chin Pei Yee, Haviluddin Haviluddin, Yuto Lim

“…The quality of data collected from sensors greatly influences the performance of the modelling processes using ML algorithms. These three elements (e.g., BD, ML and IoT) have been used tremendously to improve all areas of rice production processes in agriculture, which transform traditional rice farming practices into a new era of rice smart farming or rice precision agriculture. …”
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Optimization of biodiesel production from rice bran oil by ultrasound and infrared radiation using ANN-GWO by Sebayang, A.H., Kusumo, F., Milano, J., Shamsuddin, A.H., Silitonga, A.S., Ideris, F., Siswantoro, J., Veza, I., Mofijur, M., Reen Chia, S.

“…In this study, biodiesel from RBO was produced via transesterification, and the process variables were optimized using the combination of ANN and GWO algorithm. …”
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Hyperspectral imaging for detection of macronutrients retained in glutinous rice under different drying conditions by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah, Megat Ahmad Azman, Puteri Nurain, Onwude, Daniel I.

“…Subsequently, predictive models were developed based on processed spectra for the detection of the macronutrients, which include protein content (PC), moisture content (MC), fat content (FC), and ash content (AC). …”
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Optimization of biodiesel production from rice bran oil by ultrasound and infrared radiation using ANN-GWO by Sebayang A.H., Kusumo F., Milano J., Shamsuddin A.H., Silitonga A.S., Ideris F., Siswantoro J., Veza I., Mofijur M., Reen Chia S.

“…In this study, biodiesel from RBO was produced via transesterification, and the process variables were optimized using the combination of ANN and GWO algorithm. …”

Estimation of microclimate parameters on infestation rate of yellow stem borer (Scirpophaga incertulas) on MR297 rice variety by Idris, Dauda

“…Rice is the second highestyielding grain and a staple diet in most countries. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan T., Manan T.S.B., Isa M.H., Ghanim A.A.J., Beddu S., Jusoh H., Iqbal M.S., Ayele G.T., Jami M.S.

Cr(VI) adsorption from aqueous solution by an agricultural waste based carbon by Khan, T., Isa, M.H., Ul Mustafa, M.R., Yeek-Chia, H., Baloo, L., Binti Abd Manan, T.S., Saeed, M.O.

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Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

“…The simplified ANFIS controller was then applied to control the developed ANFIS-based dryer model using different initial conditions based on real data. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.

“…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann) by Khan, Taimur, Abd Manan, Teh Sabariah, Hasnain Isa, Mohamed, A. J. Ghanim, Abdulnoor, Beddu, Salmia, Jusoh, Hisyam, Iqbal, Muhammad Shahid, Ayele, Gebiaw T, Jami, Mohammed Saedi

“…The Fletcher–Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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