Search Results - (( data processing model algorithm ) OR ( java _ normalization algorithm ))
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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Thesis -
2
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…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. …”
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3
Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing
Published 2016“…The designed modules is in the form of algorithms, GridSim, Java Development Kits and Java Language used to support the design process whereas the Netbeans software serves as the platform to simulate the experiment so as to obtain the results. …”
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4
SANAsms: Secure short messaging system for secure GSM mobile communication
Published 2008“…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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5
Mapreduce algorithm for weather dataset
Published 2017“…The well-known method for Big Data analytics is MapReduce Model. Nevertheless, the usage of MapReduce Model in processing weather dataset is not widely explored. …”
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6
MapReduce algorithm for weather dataset
Published 2018“…The well-known method for Big Data analytics is MapReduce Model. Nevertheless, the usage of MapReduce Model in processing weather dataset is not widely explored. …”
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Research Report -
7
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to create parameters, there are many problems arise in the process of fuzzy modeling. The problems are data incomplete and the size of the data is large. …”
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Undergraduates Project Papers -
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
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9
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…To avoid such overheads many techniques have been used, however in this thesis stream-based data processing model is used in which data is processed in the form of continuous instances of data items. …”
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10
Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…In this thesis, a new quaternion gradient based adaptive algorithm for FIR adaptive filter is developed. The proposed algorithm is capable of processing the generality of quaternion and complex data signals in both noisy and noise-free environments. …”
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11
SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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12
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 -
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Conference or Workshop Item -
14
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Development of decentralized data fusion algorithm with optimized kalman filter.
Published 2016“…The model collaborates data fusion technology with algorithm engineering domain, accordingly data fusion algorithm is optimized using sophisticated technique such as functional programming to reduce the processing delay and memory usage. …”
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17
Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting
Published 2021“…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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18
Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Industrial process time series data could be processed with ease by deep learning algorithms, particularly transformer-based models because of their multi-head attention mechanism. …”
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Article -
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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok
Published 2019“…This development corresponds to the windstorm hazard monitoring mechanism which is not available in the country. The predictive model includes 16 prediction processes with 20 back-propagation algorithms whereby radar imageries and meteorological station data were used as a raw data input. …”
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20
Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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