Search Results - (( java application _ algorithm ) OR ( ((data integration) OR (co integration)) data algorithm ))
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1
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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Thesis -
2
A machine learning approach to tourism recommendations system
Published 2025“…This project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. …”
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Final Year Project / Dissertation / Thesis -
3
Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.]
Published 2018“…The integration approach between MSC Adams/Car and Matlab/Simulink known as co-simulation or Software in the Loop (SiL), involve multiple solvers in one computational loop. …”
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4
AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. …”
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5
Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm
Published 2025“…Future work may focus on integrating real-time data, adjusting algorithm parameters and hybridizing ABC algorithm with other metaheuristics to further improve performance.…”
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Student Project -
6
Evaluation of arima and ann stream analytics for air quality monitoring system
Published 2021“…The data stored in the query table act as input to the analytics algorithm, which runs in R-server as well. …”
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Thesis -
7
Increasing data storage of coloured QR code using CoMMT technique
Published 2020“…The CoMM is realized in a coloured QR Code to store American Standard Code for Information Interchange (ASCII) text data. …”
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Article -
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Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines
Published 2019“…Over recent years, a lot of money have been spent by the oil and gas industry to maintain pipeline integrity, specifically in handling CO 2 internal corrosion. …”
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Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines
Published 2019“…Over recent years, a lot of money have been spent by the oil and gas industry to maintain pipeline integrity, specifically in handling CO2 internal corrosion. …”
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10
Development of genetic algorithm-based fuzzy rules design for metal cutting data selection
Published 2002“…The authors have developed fuzzy models for machinability data selection (Int. J. Flexible Autom. Integrated Manuf. 5 (1 and 2) (1997) 79). …”
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11
Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…Association analysis was employed to integrate more than one type of biological information in the same transaction database, and also to identify groups of genes that are frequently co-occurred in target samples. …”
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Thesis -
12
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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13
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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14
AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. …”
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Article -
15
Data driven hybrid evolutionary analytical approach for multi objective location allocation decisions: Automotive green supply chain empirical evidence
Published 2018“…A multi-objective mathematical model is formulated in this paper to solve a location-allocation problem in a multi-echelon supply chain network to optimize three objectives simultaneously such as minimization of total supply chain cost (TSCC), maximization of fill rate and minimization of CO2 emissions. Data driven hybrid evolutionary analytical approach is proposed by integrating Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) to handle multiple objectives into Differential Evolution (DE) algorithm. …”
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16
A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi
Published 2015“…The second layer is termed Sentiment Integration Layer, which integrates sentiment analysis capability into the algorithm by proposing a sentiment weight by the name of SumScore that reflects investors’ sentiment. …”
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Thesis -
17
Smart student timetable planner
Published 2025“…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. …”
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Final Year Project / Dissertation / Thesis -
18
An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions
Published 2024“…The proposed approach's effectiveness is evaluated within an IEEE 14-bus configuration with five microgrids (MGs) integrated with RESs using real load data from Perlis, Malaysia. …”
Conference Paper -
19
Survival analysis for the identified cancer gene subtype from the co-clustering algorithm
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Conference or Workshop Item -
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Modeling of CO emissions from traffic vehicles using artificial neural networks
Published 2019“…The hybrid model was developed based on the integration of GIS and the optimized Artificial Neural Network algorithm that combined with the Correlation based Feature Selection (CFS) algorithm to predict the daily vehicular CO emissions and generate prediction maps at a microscale level in a small urban area by using a field survey and open source data, which are the main contributions to this paper. …”
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