Search Results - (( ((_ processing) OR (data processing)) data algorithm ) OR ( java application need algorithm ))
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1
Direct approach for mining association rules from structured XML data
Published 2012“…Efforts are made to develop a new tool or method for extracting information from XML data directly without any preprocessing or post processing of the XML documents. …”
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Thesis -
2
Automated time series forecasting
Published 2011“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Monograph -
3
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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4
Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin
Published 2019“…The result of this project is all algorithm for visualizing data is functioning and the output produced from the system is correct and effective. …”
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5
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 -
6
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 -
7
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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8
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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Article -
9
Mapreduce algorithm for weather dataset
Published 2017“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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10
An efficient parallel clustering algorithm on big data using Spark
Published 2022“…Proposed algorithm gives the fast and iterative data processing and eliminates the effect of batch processing.…”
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Article -
11
MapReduce algorithm for weather dataset
Published 2018“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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Research Report -
12
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…Experimental results are compared with other alternative online/offline hybrid density-based clustering algorithms. The average processing time for data point in the data stream is about 2 milliseconds which is much lower than the aligned clustering algorithms in literature. …”
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13
Association ruleset formulation for cyberattack attribution process in cyber threat intelligence using apriori algorithm
Published 2021“…In data preprocessing, a clean and useful data is produced and become as an input for association analysis process. …”
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Thesis -
14
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 -
15
Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…Subsequently, the integration of embedded correlation-based filtering algorithm has further increased the classification accuracy of training process and testing process by 4.93% and 14.73% respectively. …”
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16
Optimized clustering with modified K-means algorithm
Published 2021“…Besides, huge data often face with correlated variables which lead to incorrect clustering process. …”
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17
The implementation of post-processing data thinning for multibeam echo sounding data
Published 2006“…Comparisons on the final results based on these three algorithms will be discussed in order to decide which algorithm is most favorable to be used in post-processing data thinning for cleaned MBES dataset. …”
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Conference or Workshop Item -
18
An efficient real-time terrain data organization and visualization algorithm based on enhanced triangle-based level of detail technique
Published 2006“…According to the results obtained during the pre-processing, the partitioning of digital elevation data into tiles has successfully reduced the data size although it required a longer processing time. …”
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Thesis -
19
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…Problem of the size of data happen when data cannot be process because of it too complex. …”
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Undergraduates Project Papers -
20
Enhanced kiosks mapping on traditional market using Apriori Algorithm / Ardiansyah Dores, and Tazkiyah Herdi
Published 2021“…The algorithm used here is a priori algorithm, the data used are questionnaire data from 250 respondents, from the data taken 120 data used as training data, for the process of making data models. …”
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