Search Results - (( developing ((a missing) OR (_ missing)) algorithm ) OR ( java implication based algorithm ))

Missing tags detection algorithm for radio frequency identification (RFID) data stream by Zainudin, Nur 'Aifaa

“…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
Get full text
Get full text
Get full text
Get full text

Detection Of Misplaced And Missing Regions In Image Using Neural Network by Tan , Jin Siang

“…Therefore, it is necessary to develop an algorithm that is able to detect both misplaced and missing jigsaw puzzles. …”
Get full text
Get full text

An Evaluation of Machine Learning Algorithms for Missing Values Imputation by Kohbalan, Moorthy, Ali, Mohammed Hasan, Mohd Arfian, Ismail, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris

“…Hence, it is necessary to resolve this problem of missing values imputation. Our research paper presents a review of missing values imputation approaches. …”
Get full text
Get full text
Get full text

Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
Get full text
Get full text

Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

Get full text
Get full text
Get full text

Development of an imputation technique - INI for software metric database with incomplete data by Wasito, Ito, Olanrewaju, Rashidah F.

“…Missing data causes significant problem. With inaccurate data or missing data, it is very difficult to know how much a project will cost or worth. …”
Get full text
Get full text
Get full text

Missing-values imputation algorithms for microarray gene expression data by Moorthy, Kohbalan, Jaber, Aws Naser, Mohd Arfian, Ismail, Ernawan, Ferda, Mohd Saberi, Mohamad, Safaai, Deris

“…In gene expression studies, missing values are a common problem with important consequences for the interpretation of the final data (Satija et al., Nat Biotechnol 33(5):495, 2015). …”
Get full text
Get full text
Get full text
Get full text
Get full text
Get full text

MISSING DAILY RAINFALL PREDICTION USING GREY WOLF OPTIMIZER-BASED NEURAL NETWORK by Lai, Wai Yan, Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Muhammad Khusairy, Bakri

“…This research chapter presents the integration of the Grey Wolf Optimizer (GWO) algorithm for training a Feedforward Neural Network (FNN) to address the issue of missing daily rainfall records. …”
Get full text
Get full text
Get full text

Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

“…The primary focus is on developing a novel data-driven approach for modeling continuous-time Hammerstein models, particularly in the presence of missing output data. …”
Get full text
Get full text
Get full text

Imputation Analysis of Time-Series Data Using a Random Forest Algorithm by Nur Najmiyah, Jaafar, Muhammad Nur Ajmal, Rosdi, Khairur Rijal, Jamaludin, Faizir, Ramlie, Habibah, Abdul Talib

“…Missing data poses a significant challenge in extensive datasets, particularly those containing time-series information, leading to potential inaccuracies in data analysis and machine learning model development. …”
Get full text
Get full text
Get full text
Get full text

New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Another challenge is how to solve the problem of missing data. Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. …”
Get full text
Get full text

Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

“…Missing data is a widespread data quality issue across various domains. …”
Get full text
Get full text
Get full text

DEVELOPMENT OF MULTI-VERSE OPTIMIZER IN ARTIFICIAL NEURAL NETWORK FOR ENHANCING THE IMPUTATION ACCURACY OF DAILY RAINFALL OBSERVATIONS by Lai, Wai Yan, Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman

Get full text
Get full text
Get full text

Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network by Dayang Suhaila, Awang Suhaili

“…ANN was chosen based on its ability to extract the relation between the inputs and outputs of a process without the physics known explicitly.In this study, the ANN was developed specifically to predict the daily missing precipitation and data simulated are utilized to optimize prediction accuracy for daily water level. …”
Get full text
Get full text
Get full text

A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts by Nur Faiqah ‘Aqilah binti Fuaad

Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

“…Missing data is a widespread data quality issue across various domains. …”
Get full text
Get full text
Get full text

Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

“…The overall accuracy of counting existing oil palm trees using the approach developed in this study is 93.3% while missing trees detection gives the detection accuracy of 89.2%. …”
Get full text
Get full text

Investigation of the Effects of Imputation Methods for Gene Regulatory Networks Modelling Using Dynamic Bayesian Networks by Sin, Yi Lim, Mohd Saberi, Mohamad, Lian, En Chai, Safaai, Deris, Weng, Howe Chan, Sigeru, Omatu, Muhammad Farhan, Sjaugi, Muhammad Mahfuz, Zainuddin, Gopinathaan, Rajamohan, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…Several missing value imputation methods have been developed to overcome the problems. …”
Get full text
Get full text
Get full text

Neural Network with Genetic Algorithm Prediction Model of Energy Consumption for Billing Integrity in Gas Pipeline by Hasbullah, Aidil Fazlina Binti

“…Along the development of oil and gas industry, missing data is one of the contributors that restrains in analyzing and processing data task in database. …”
Get full text
Get full text

An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

“…While TSE estimates the missing data in traffic states, such as speed and density to reduce data sparsity, TSP uses the traffic data to forecast the traffic state within a certain time period in future. …”
Get full text
Get full text
Get full text