Search Results - (( knowledge relation tree algorithm ) OR ( java adaptation optimization algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…This algorithm provides a decision tree output to represent the knowledge model, enabled a faster classification of intra-urban classes, and disabled the subjectivities which are related to the interaction of the analyst. …”
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3
Modeling forest fires risk using spatial decision tree
Published 2011“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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4
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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5
Hotspot occurences classififcation using decision tree method: case study in the Rokan Hilir, Riau Province, Indonesia
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6
Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
7
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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8
Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining
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9
A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection
Published 2022“…Meanwhile, for improving the efciency of training and predicting, Pearson Correlation analysis, standard deviation, and a new adaptive K-means are used to select attributes and make fuzzy interval decisions. The proposed algorithm was trained, validated, and tested on the NSL-KDD (National security lab–knowledge discovery and data mining) dataset. …”
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10
Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis
Published 2017“…The predictive model was developed using Induction Decision Tree (ID3) algorithm, a popular data mining technique an exploratory tool for knowledge discovery. …”
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11
Classification Analysis Of The Badminton Five Directional Lunges
Published 2018“…Lunge type patterns were related to ID and GT. Conclusively, the identity, game reaction time and type of lunge were found being the key determinants for badminton lunge classification accounting for highest classification accuracy in REP Tree algorithm.…”
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12
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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13
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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14
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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15
Finger Motion In Classifying Offline Handwriting Patterns
Published 2017“…The preprocessed data is classified using the J48 tree algorithm. The correctly classified accuracy prediction after trained could achieve up to 98 %, Finding revealed that the angle of thumbs plays a significant role in classification of the inclination of the English sentence.…”
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16
Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization
Published 2022“…One of the two input features is P (bar) and the other is T (k). ADA-DT (Adaboost Algorithm Decision Tree), ADA-LR (Adaboost Algorithm-Linear Regresion), and ADA-GRNN (Generative Regression Neural Network) models showed MAE of 6.54 ˣ 10ˉ⁵, 4.66 10 ˉ⁵, and 8.35 10 ˉ⁵, respectively. …”
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17
Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing
Published 2015“…In this research, to eliminate the manual developments of the rule-sets, the supervised DM technique was used to identify the appropriate selection of attributes for object-based classification. This algorithm represents the decision tree knowledge model, enables fast classification of intra-urban classes, and disables subjectivities related to the interaction with analysts. …”
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18
Content-based indexing of low resolution documents
Published 2016“…The algorithm has the capability of reducing any shortcoming associated with normalisation in initial fusion technique. …”
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19
A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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20
Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset
Published 2020“…This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using several well-known machine learning algorithm such as Decision Tree, Support Vector Machine and Naïve Bayers. …”
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