Search Results - (( using spatial data algorithm ) OR ( evolution optimization svm algorithm ))
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1
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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2
An extended ID3 decision tree algorithm for spatial data
Published 2011“…Utilizing data mining tasks such as classification on spatial data is more complex than those on non-spatial data. …”
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3
Classification model for hotspot occurrences using spatial decision tree algorithm
Published 2013“…Empirical result demonstrates that the proposed algorithm can be used to join two spatial objects in constructing a spatial decision tree from a spatial dataset. …”
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4
Clustering Spatial Data Using a Kernel-Based Algorithm
Published 2005“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data. …”
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5
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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6
Extended spatial decision tree algorithm for classifying hotspot occurrence
Published 2013“…The proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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7
Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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8
Classification with degree of importance of attributes for stock market data mining
Published 2004“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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9
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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10
Hybrid Spatial-Artificial Intelligence Approach for Renewable Energy Sources Sites Identification and Integration in Sarawak State
Published 2022“…It is followed by identifying RES sites using spatial data and Multi-Criteria Decision Making-Analytical Hierarchy Process (MCDM-AHP) algorithm. …”
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Thesis -
11
A decision tree based on spatial relationships for predicting hotspots in peatlands
Published 2014“…The spatial tree has produces higher accuracy than the non-spatial trees that were created using the ID3 and C4.5 algorithm. …”
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12
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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13
A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube
Published 2023“…To fill this gap, an online clustering algorithm for handling evolving data streams using a tempo?…”
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The design and implementation of a two and three-dimensional triangular irregular network based GIS
Published 2000“…The impediments which relate to spatial data especially data representation, data structuring and datamodelling using object-oriented (OO) techniques are the foci of this thesis. …”
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15
Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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16
Impact of BPL penalty functions and PSF models in PET/CT radial spatial resolution recovery
Published 2024“…Additionally, different reconstruction algorithms' impact on spatial resolution within PET/CT FOV was assessed using standard deviation calculations and plotting error bars to show spreading of the data around the mean as well as to determine the significant difference between the FWHM measured using different types of reconstruction. …”
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An intelligent system based on kernel methods for crop yield prediction
Published 2006“…The algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield. …”
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18
Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification
Published 2017“…For example, Binary Particle Search Optimization Common Spatial Pattern (BPSO-CSP) was proposed to choose multiple possible best bands to be used in processing the data. …”
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19
SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS
Published 2016“…The purpose of this research is to create an ArcGIS spatial data mining toolbox for mapping the suitability of landfill sites at a regional scale using neural networks. …”
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Finding spatio-temporal patterns in climate data using clustering
Published 2005“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data.…”
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