Search Results - (( java implication based algorithm ) OR ( missing prices using algorithm ))

Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi by Mohd Azmi, Nur Amirah

“…Traditional methods struggle to model these complexities effectively, necessitating adoption of advanced algorithms to improve accuracy. The aim of this project is to develop a Diamond Price Prediction System using Random Forest, designed to accurately predict diamond prices based on attributes. …”
Get full text
Get full text

Computationally efficient single layer transformer convolutional encoder for accurate price prediction of agriculture commodities by Bundak, Caceja Elyca, Abd Rahman, Mohd Amiruddin, Mohd Haniff, Nurin Syazwina, Afrizal, Nur Syaiful, Yusof, Khairul Adib, Abdul Karim, Muhammad Khalis, Mamat, Md Shuhazlly, Rahmat, Romi Fadillah

“…Additionally, since time-series price data normally comes with missing values, this study introduce a sequence nearest neighbor imputation algorithm for anchoring that data to complement the STCE method. …”
Get full text
Get full text
Get full text

A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting by Razak I.A.W.A., Abidin I.Z., Yap K.S., Abidin A.A.Z., Rahman T.K.A., Nasir M.N.M.

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. …”

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

An hour ahead electricity price forecasting with least square support vector machine and bacterial foraging optimization algorithm by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A., Baharin N., Jali M.H.B.

“…So far, no works has been established on multistage feature and parameter optimization using LSSVM-BFOA for hour-ahead price forecast. The model was examined on the Ontario power market. …”

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

Get full text
Get full text
Get full text

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush