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1
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
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2
Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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3
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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4
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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5
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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6
An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…This research designed an anomaly-based detection, by adopting the modified Cuckoo Search Algorithm (CSA), called Mutation Cuckoo Fuzzy (MCF) for feature selection and Evolutionary Neural Network (ENN) for classification. …”
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A fuzzy approach for early human action detection / Ekta Vats
Published 2016“…In order to perform early human action detection, the conventional classification problem is modified into frame-by-frame level classification. …”
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8
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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9
A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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10
The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…However, none of the available works had proposed BFOA as a classification algorithm despite of its good performance. …”
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11
MODIFIED AIS-BASED CLASSIFIER FOR MUSIC GENRE CLASSIFICATION
Published 2010“…The discussion will detail out the MIC procedures applied and the modified part in solving the classification problem. …”
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Conference or Workshop Item -
12
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…In this thesis rough sets approach was used in the preprocessing stages, namely in the vector quantization operation in which feature vectors are quantized or classified to a finite set of codebook classes. Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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13
Mutable composite firefly algorithm for gene selection in microarray based cancer classification
Published 2022“…Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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14
Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…For optimum results in performance analyses, the technique was evaluated using nine datasets: five datasets were artificially generated, while four were real-world datasets sourced from KEEL over MCPSO and IMCPSO algorithms. …”
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15
A novel islanding detection technique using modified Slantlet transform in multi-distributed generation
Published 2019“…A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…The proposed approachoutperforms existing available meta-heuristic algorithms. Specifically, the proposed model achieved 97% classification rate, 95% precise prediction and less than 2.0 error rate. …”
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18
Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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Attacks detection in 6G wireless networks using machine learning
Published 2023“…The voting average method is used as an aggregation step, and two classifiers—Random Forest (RF) and Support Vector Machine (SVM)—are modified to be used as ML Algorithms. The proposed method shown an outperformed the existing classification method. …”
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Proceeding Paper -
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EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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