Search Results - (( data optimization based algorithm ) OR ( variables classification system algorithm ))*
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1
A genetic algorithm based fuzzy inference system for pattern classification and rule extraction
Published 2023“…This paper presents a genetic-algorithm-based fuzzy inference system for extracting highly comprehensible fuzzy rules to be implemented in human practices without detailed computation (hereafter denoted as GA-FIS). …”
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2
Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
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3
A new integrated approach for evaluating sustainable development in the electric vehicle sector
Published 2025“…This study identifies the relative importance of the classification attribute variables based on the classification rules of the target attributes by conducting further analysis with the CART decision model and constructs an optimal prediction model.…”
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4
Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…The developed algorithms interpret raw IR-UWB radar sensor data and associate it with specific hand gestures, addressing the core objective of gesture recognition. …”
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5
Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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6
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). …”
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7
Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…Approaches for the early prediction of flash floods and hurricanes may be categorized as (a) Modeling of the system (bathymetry), (b) Sensors and gauges-based measurement, (c) Radar-based images, (d) Satellite images and data, and (e) AI-based prediction. …”
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8
Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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9
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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10
Observer-based fault detection with fuzzy variable gains and its application to industrial servo system
Published 2020“…This work is interested in proposing an observer with fuzzy variable gains for a general nonlinear system. Furthermore, a linear model has been built to facilitate the accomplishment of the fault detection of the industrial servo system by using the proposed observer. …”
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11
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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12
Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…In the next phase, the SVM classifier was trained to achieve the best classification using training data and test data integrated with selected features. …”
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13
A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the hybrid fuzzy clustering and Apriori algorithm technique, respectively. …”
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14
Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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15
Lightning fault classification for transmission line using support vector machine
Published 2023“…Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. …”
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16
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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17
Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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18
Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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19
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…Thus, there is a need for an automated recognition system to reduce the variability and increase the reliability of the test results. …”
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