Search Results - (( developing quantity selection algorithm ) OR ( java application stemming algorithm ))

Experimental Investigation and Optimization of Minimum Quantity Lubrication for Machining of AA6061-T6 by Najihah, Mohamed, M. M., Rahman, K., Kadirgama

“…Process parameters including the cutting speed, depth of cut, feed rate and MQL flow rate are selected for study to develop an optimization model for flank wear based on the genetic algorithm. …”
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Scheduling of batch process plant / Abdul Aziz Abu Bakar by Abu Bakar, Abdul Aziz

“…This research work is devoted to software development of scheduling and control algorithm of batch process plant using shortest path method developed by Dijkstra and K* shortest path method developed by Jin Y. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

“…A machine learning algorithms, SVM have been used to build species identification models. …”
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SOC Estimation Using Deep Bidirectional Gated Recurrent Units with Tree Parzen Estimator Hyperparameter Optimization by How D.N.T., Hannan M.A., Lipu M.S.H., Ker P.J., Mansor M., Sahari K.S.M., Muttaqi K.M.

Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari by Mozafar , Ansari

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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

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Short term electricity price forecasting with multistage optimization technique of LSSVM-GA by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A.

“…Therefore, a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features. …”

Short Term Electricity Price Forecasting With Multistage Optimization Technique Of LSSVM-GA by Wan Abdul Razak, Intan Azmira, Zainal Abidin, Izham, Keem Siah, Yap, Zainul Abidin, Aidil Azwin, Abdul Rahman, Titik Khawa

“…Price prediction has now become an important task in the operation of electrical power system.In short term forecast,electricity price can be predicted for an hour-ahead or day-ahead.An hour-ahead prediction offers the market members with the pre-dispatch prices for the next hour.It is useful for an effective bidding strategy where the quantity of bids can be revised or changed prior to the dispatch hour.However,only a few studies have been conducted in the field of hour-ahead forecasting.This is due to most of the power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than singlesettlement system (real time).Therefore,a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features.So far,no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for hour-ahead price prediction.All the models are examined on the Ontario power market;which is reported as among the most volatile market worldwide.A huge number of features are selected by three stages of optimization to avoid from missing any important features.The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models.…”
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Oil palm maturity classifier using spectrometer and machine learning by Goh, Jia Quan

“…Normalized Difference Vegetation Index (NDVI) is selected as the best prediction model with 93.8% classification accuracy. …”
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Design and development of detection scheme using multiline image scanning for aerial mapping of a simulated rice paddy field and implemented on unmanned aerial vehicle / Mohamad Fa... by Misnan, Mohamad Farid

“…Thus, two dimensional (2D) online mapping was purposed for this research and suitable image processing technique was developed. In producing the map of desired place of a paddy field, a suitable sensor has to be selected to sense the required desired features. …”
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Development of wireless data acquisiton system using LoRa technology for construction of PID control system by Al Sayed Noor Mohamed A Jassem

Design and development of detection scheme using multiline image scanning for aerial mapping of a simulated rice paddy field and implemented on unmanned aerial vehicle / Mohamad Fa... by Misnan, Mohamad Farid

“…Thus, two dimensional (2D) online mapping was purposed for this research and suitable image processing technique was developed. In producing the map of desired place of a paddy field, a suitable sensor has to be selected to sense the required desired features. …”
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Monitoring and determination of CO2 by using optical fibre sensor and artificial neural network / Faiz Bukhari Mohd Suah, Abdul Mutalib Md Jani and Siti Aminah Md Ali by Mohd Suah, Faiz Bukhari, Md Jani, Abdul Mutalib, Md Ali, Siti Aminah

“…concentration, although there is no difference under 0 1% CO2 gas concentration The sensitivity of the sensor increases with the increase in the dye concentration The relative humidity and the film composition have an important effect on the attenuation difference The application of artificial neural network (ANN) in signal processing of optical fibre pH sensor is presented The pH sensor is developed based on the use of bromophenol blue indicator immobilized in a sol-gel thin film as a sensing material A three layer feed-forward network was used and the network training was performed using the back-propagation (BP) algorithm Spectra generated from the pH sensor at several selected wavelengths are used, as the input data for the ANN. …”
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The effect of human learning and forgetting on fuzzy EOQ model with backorders / Nima Kazemi by Nima , Kazemi

“…In order to optimize the models and derive solutions, an optimization algorithm was developed for the first model and applied later throughout the study. …”
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Gas Emission Prediction for Environmental Sustainability via Heterogeneous Data Sources Correlation with Support Vector Regression by Chen C.P., Tiong S.K., Koh S.P., Chooi Albert F.Y., Mohd Yapandi M.F.K.

Performance investigation and multi-objective optimization of end milling of aluminium alloy 6061 T6 with coated and uncoated carbide tools under various cooling conditions by Syeda Najiha, Masood

“…Comprehensive multi-objective optimization model using genetic algorithm is developed to optimize machining performance measures under different MQL conditions, based on Pareto optimal design approach. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

“…The increasing volumes of electronic healthcare records (EHR) encourage the development of the application and research of machine learning (ML) in digital health. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…Therefore, we automated the development of such resources at scale to alleviate the lag time and the cost normally associated with their procurement. …”
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