Search Results - (( using rice method algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Mathematical modelling of rice mill production by using cubic B-spline and discrete least square method / Siti Noorkhaliesa Che Pa by Che Pa, Siti Noorkhaliesa

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Ensemble and single algorithm models to handle multicollinearity of UAV vegetation indices for predicting rice biomass by Derraz, Radhwane, Muharam, Farrah Melissa, Nurulhuda, Khairudin, Ahmad Jaafar, Noraini, Keng Yap, Ng

“…Conventional sampling methods predict rice biomass accurately. However, these methods are destructive, time-consuming, expensive, and labour-intensive. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Applying multi-objective genetic algorithm (MOGA) to optimize the energy inputs and greenhouse gas emissions (GHG) in wetland rice production by Elsoragaby, S., Yahya, A., Mahadi, M.R., Nawi, N.M., Mairghany, M., M Elhassan, S.M., Kheiralla, A.F.

“…The developed multi-objective genetic algorithm (MOGA) model, showed an excess of energy inputs used by the farmers more than the required energy by 37.8 and 40 for the transplanting and broadcast seeding methods. …”
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Comparison of conjugate gradient methods for developing the multiple linear regression model for rice production in Malaysia / Nur Atikah Mustapha by Mustapha, Nur Atikah

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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 redundant wavelength was removed and the wavelength features that are strongly associated with the moisture content of glutinous rice were chosen using the competitive adaptive reweighted sampling algorithm (CARS). …”
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Optimization of energy inputs and greenhouse gas emissions of wetland rice cultivation in Malaysia by Elsoragaby, Suha Gaafar Babekir

“…Later, the energy inputs and GHG emissions were optimized using the multi objective genetic algorithm (MOGA) analysis techniques. …”
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Rapid and non-destructive monitoring of the drying process of glutinous rice using visible-near infrared hyperspectral imaging by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah

“…Different preprocessing methods and effective wavelength selection techniques were used to eliminate the noise and redundant wavelength in the reflectance spectra, and predictive models were developed for the glutinous rice quality. …”
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A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms by Ghazvini, Anahita, Mohd Sharef, Nurfadhlina, Balasundram, Siva Kumar, Lee, Lai Soon

“…The proposed method can be replicable in other low-resourced crop digital twin system.…”
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A concentration prediction-based crop digital twin using nutrient co-existence and composition in regression algorithms by Mohd Sharef, Nurfadhlina, Balasundram, Siva Kumar, Lai, Soon Lee, Ghazvini, Anahita

“…The proposed method can be replicable in other low-resourced crop digital twin system.…”
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A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework by Bari, Bifta Sama, Islam, Md Nahidul, Rashid, Mamunur, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Musa, Rabiu Muazu, Ahmad Fakhri, Ab. Nasir, Majeed, Anwar P.P. Abdul

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Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia by Mohd Nasir, Muhammad Adib, Harun, Sobri, Zainuddin, Zaitul Marlizawati, Kamal, Md Rowshon, Che Rose, Farid Zamani

“…Two machine learning algorithms, named Support Vector Regression (SVR) and Random Forest (RF), were applied to predict ETo and rice irrigation requirements using only climatic data (rainfall, temperature, relative humidity, and wind speed). …”
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Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.] by Mohammud, Mohd Mahadzir, Mohamad Bakre, Muhammad Syaham, Mohd Fohimi, Nor Azirah, Rabilah, Rosniza, Ahmad, Muhammad Iqbal

“…The goals are to predict the output producer gas using an algorithm and to compare the trained prediction result with actual experiment data for rice husk gasification. …”
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Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

“…Conventional rice sampling methods are effective. However, they are destructive, laborious, time-consuming, impractical for large fields, and subject to human error. …”
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