Search Results - (( based optimization based algorithm ) OR ( data extraction based algorithm ))
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1
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…Experimental results are compared with other alternative online/offline hybrid density-based clustering algorithms. The average processing time for data point in the data stream is about 2 milliseconds which is much lower than the aligned clustering algorithms in literature. …”
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2
Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…Nonetheless, the optimal parameter settings for the watershed algorithm need to be adjusted based on stand density. …”
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3
A buffer-based online clustering for evolving data stream
Published 2019“…In this study, we present a fully online density-based clustering algorithm called buffer-based online clustering for evolving data stream (BOCEDS). …”
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4
Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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5
Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman
Published 2022“…In this work, we present a robust adaptive Arithmetic Optimization Algorithm based on the adaptive damping Berndt-hall-hall-Hausman (RaAOAAdBHHH) approach to efficacity determine the parameters of the single, double, and three diode PV model. …”
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7
BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Prior to developing the whole multilayered ensemble framework, two separate experiments were performed to evaluate and study the different methods of feature extraction and selection. Methods of feature extraction can be separated into word based and phrase based. …”
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9
GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators
Published 2024“…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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11
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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12
An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…In this paper, we propose an efficient IDS based on hybrid heuristic optimization algorithm which is inspired by magnetic field theory in physics that deals with attraction between particles scattered in the search space. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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14
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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15
An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…In this paper, we propose an efficient IDS based on hybrid heuristic optimization algorithm which is inspired by magnetic field theory in physics that deals with attraction between particles scattered in the search space. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…The optimized DBN algorithm, known as the HW-DBN algorithm, integrated through feature learning based on a Gaussian–Bernoulli Restricted Boltzmann Machine as well as classification task through a weight neuron network. …”
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19
Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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Conference or Workshop Item -
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A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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