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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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2
Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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3
Mobile Learning: An Application Prototype for AVL Tree Learning Object
Published 2010“…Hence, we have seen the number of students enrolled for computer science related programs has decreased lately. Current delivery methods for computer science concepts are found not to be interesting to the students. …”
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Mobile Learning: An Application Prototype for AVL Tree Learning Object
Published 2010“…Hence, we have seen the number of students enrolled for computer science related programs has decreased lately. Current delivery methods for computer science concepts are found not to be interesting to the students. …”
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Enhancing understanding of programming concepts through physical games
Published 2017“…We produced in total 10 lesson games to illustrate variables, swapping, arrays, sorting algorithm particularly bubble sort, quicksort, selection sort, graph theory, dynamic programming, amortized analysis and trees. …”
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Petri Net Algorithm for controlling and monitoring system
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…ML can examine millions of data sets in a short period of time without being explicitly programmed to improve the results. This type of algorithm can aid financial institutions in making grant selections for their clients. …”
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Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques
Published 2021“…Therefore, in this research an algorithm has been created which can achieve the following goals. 1) To generate DTM only with LiDAR data without the need for layers and other information from the area 2) To create a building footprint from the LiDAR data by removing the tree cover effect 3) To create an automatic system that can perform the production process of DTM and footprint without the intervention of an expert. …”
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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13
Random Amplified Polymorphic DNA Analysis of Four Breeds of Sheep in Malaysia
Published 1999“…Genetic distance between populations ranged from 0.1040 to 0.1357 based on the Dice's algorithm while the distance based on the Jaccard's algorithm ranged from 0.1875 to 0.2381. …”
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