Search Results - (( data application using algorithm ) OR ( pre evaluation method algorithm ))
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1
Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Thesis -
2
A new ant based rule extraction algorithm for web classification
Published 2011“…Methods to reduce the number of attributes and discretization are two important data pre-processing steps before the data can be used for classification activity. …”
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Monograph -
3
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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4
Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
Published 2018“…In this study, the uncertainty and nonstationary characteristics of streamflow data has been treated using a set of coupled data pre-processing methods before being considered as input for an artificial neural network algorithm namely; rolling mechanism (RM) and grey models (GM). …”
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Article -
5
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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Final Year Project / Dissertation / Thesis -
6
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…The designed algorithms are implemented for EHD equations and their performance is evaluated by using different performance indicators. …”
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7
Rainfall prediction system using Artificial Neural Network (ANN) / Izzat Izzuddin Zulkarnain
Published 2024“…The methodology employed a systematic approach, including data collection, pre-processing, prototype architecture design, algorithm implementation, and evaluation. …”
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8
A hybrid Method Of Centroid-Based Clustering And Meta-Heuristic For Personalized Web Search
Published 2024thesis::doctoral thesis -
9
Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…The simulation of quasi-static is used. We generate the model and evaluate the performance in MATLAB. …”
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10
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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11
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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12
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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13
M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Monograph -
14
Missing values imputation tool using imputex algorithm
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Article -
15
Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data
Published 2011“…The model works based on the seasonal values of Normalized-difference Vegetation Index (NDVT) in the study area. The algorithm was statistically compared with maximum likelihood supervised classification method. …”
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Article -
16
Feature selection methods application towards a new dataset based on online student activities / Muhammad Hareez Mohd Zaki ... [et al.]
Published 2023“…Thus, more significant features are needed to evaluate students’ performance to improve the existing method. …”
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17
Power System State Estimation In Large-Scale Networks
Published 2010“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Thesis -
18
Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
Published 2022“…Objective: This study aims to predict the academic performance of dental students based on their admission results using Artificial Intelligence. Methods: Various Machine Learning (ML) algorithms were applied using academic result samples of graduates of the Kulliyyah of Dentistry, IIUM from 2012-2017. …”
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Proceeding Paper -
19
Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
Article -
20
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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