Search Results - (( knowledge generation based algorithm ) OR ( java adaptation optimization algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
Knowledge-based genetic algorithm for multidimensional data clustering
Published 2014“…In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. …”
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3
Knowledge-based genetic algorithm for multidimensional data clustering
Published 2013“…In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. …”
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Proceeding Paper -
4
Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot
Published 2005“…This paper presents a new schema to overcome behavior-based problems based on Fuzzy Logic Controller (FLC) where the fuzzy knowledge bases are tuned automatically by Genetic Algorithm (GAs), known as Genetic Fuzzy System (GFS). …”
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5
Multiple case-based retrieval for university course timetabling problem
Published 2016“…The case-based retrieval technique is further enhanced and improvised into a new algorithm known as Multiple Case-based Retrieval. …”
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6
An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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7
A frequent pattern mining algorithm based on FP-growth without generating tree
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A frequent pattern mining algorithm based on FP-growth without generating tree
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9
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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10
Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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11
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…Then, clustering graphs are generated based on the connectivity among micro-clusters. …”
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12
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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13
Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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14
Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. …”
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15
Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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16
Fuzzy genetic algorithms for combinatorial optimisation problems
Published 2012“…Fuzzy Logic Controllers (FLCs) are considered as knowledge-based systems, incorporating human knowledge. …”
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17
A Fusion-Based Framework For Explainable Suicide Attempt Prediction
Published 2024“…An information fusion-based explanation generation method is proposed by integrating predictions to generate a prediction description to support decision-making. …”
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18
A study of density-grid based clustering algorithms on data streams
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19
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Total rules number, rules length and rules accuracy for the generation rules are recorded. 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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20
Discovering association rules for mining images datasets: a proposal
Published 2005“…A synthetic image set containing geometric shapes will generate to test the initial algorithm implementation. …”
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