Search Results - (( quantity selection method algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The second algorithm reduces the quantity of interest regions by using the Extremal Region Selection (ERS) algorithm. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…Furthermore, the proposed method had a better performance compared with the chi-square method and the ABC algorithm as a feature selection method…”
Get full text
Get full text
Get full text
Get full text
Get full text

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.

Scheduling of batch process plant / Abdul Aziz Abu Bakar by Abu Bakar, Abdul Aziz

“…Yea These methods are selected due to the practicality and wide acceptance from the experts in the field. …”
Get full text
Get full text

Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions by Ernawati, Kamal Baharin, Safiza Suhana, Kasmin, Fauziah

“…The clusters are scored using the sum weighting method. The highest valued cluster that consists of eight regencies and 18 cities that consistently contributed high quantity and quality students were selected as the priority regions. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

Shallow-water mapping at Pantai Tok Jembal, Terengganu, Malaysia, using Lansat 8 (OLI) / Nur Syahirah Hashim by Hashim, Nur Syahirah

“…The selected method is LR perform with DOS, which applies under Process C. …”
Get full text
Get full text

Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
Get full text
Get full text
Get full text
Get full text

A Risk Assessment of Transmission Line Overload Based on MLSI/PSO by Ruhaizad, Ishak, Ali, A., Nazir, Muhammad S., Malik, Muhammad Z.

“…Based on the traditional partial swarm optimization algorithm, the corresponding weights are selected according to the influence factors of each input quantity, and the calculation accuracy of the traditional point estimation method is improved to realize the overload risk assessment of transmission lines. …”
Get full text
Get full text
Get full text

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

“…Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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.

“…So far, no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for hour-ahead price prediction. …”

Oil palm maturity classifier using spectrometer and machine learning by Goh, Jia Quan

“…The reflectance data from these five parts was analyzed using statistical method and machine learning algorithm. Front equatorial was found to have significant difference between the three classes of ripeness, and an overall 92.7% of accuracy in differentiating between the maturity classes. …”
Get full text
Get full text

State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

“…State-of-charge(SOC) is a quantity that reflects the amount of available energy left in lithium-ion(Li-ion)cells. …”

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.…”
Get full text
Get full text
Get full text

Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

“…After conducting stepwise experiments and comparing with three benchmark methods - a baseline FL method and two PFL approaches in similar optimization scheme - the results shows that POLA not only systematically optimizes its internal outputs but also outperforms the comparison methods. …”
Get full text
Get full text
Get full text

A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…These expressions often deviate from the typical meaning and sequence of words, making it difficult for sentiment classifiers to accurately classify the sentiment of a tweet. Existing methods rely on manually generated sentiment lexicons for idiomatic expressions, which requires painstaking labeling of large quantities of data, limiting their scalability and accuracy. …”
Get full text
Get full text