Search Results - (( java application mining algorithm ) OR ( data classification drops algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

“…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

“…There is a need to have effective prioritization and classification of IP packets for routers to enable the forwarding of such packets including packets having critical data efficiently and with a lower drop rate. …”
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DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS by Al-Shoukry S., Jawad B.J.M., Musa Z., Sabry A.H.

“…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”

Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Electronic Tongue: Study on the Freshness of Milk by Jaafar, Mohamad Nazrin

“…After the experiment has been done, the data obtained was used in Matlab for classification purpose. …”
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Automated traffic counting data collection and analysis by Low, Anand Hong Ren

“…The performance of the algorithm is determined by the counting, classification, and speed measuring accuracy. …”
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Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

“…In this study comparing the performance classification techniques of Support Vector Machine (SVM) and C4.5 algorithms. …”
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Land Use Changes in Jeli, Kelantan by Muhammad Firdaus Abdul Karim

“…Satellite imagery are pre-processed in geometric correction and further processed in subsetting, masking cloud and supervised classification. Land use maps from supervised classification of satellite imagery and existing land use maps are then digitized into shapefile (.shp) format in ArcGIS software, spatial reference is updated to WGS1984 and accuracy assessment is performed to validate data. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

“…The second anomaly detection method is the Evolutionary Kernel Neural Network Random Weights (EKNNRW) in order to increase the accuracy of classification. The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…The LightGBM algorithm was selected for its efficiency in classification tasks, and Bayesian Optimization with Tree-structured Parzen Estimator (TPE) was employed to fine-tune its hyperparameters. …”
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Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…However, with the arrival of the deep learning era, coupled with the availability of large training data, deep learning networks have replaced the conventional networks in screening for the pterygium condition. …”
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