Search Results - ((extraction algorithm) OR (((selection algorithm) OR (genetic algorithm))))

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    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…Since there are many methods involved in each task of the multilayered ensemble, genetic algorithm is added to optimize the overall framework in order to select the optimal combinations of methods in each layer that can produce satisfactory results. …”
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    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The experimental results of the EGCACO algorithm on the UCI dataset are superior to other benchmark optimisation algorithms in terms of the number of selected features for 16 out of the 18 UCI datasets (88.89%) and the best in eight (8) (44.47%) of the datasets for classification accuracy. …”
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    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…Modifications of K-Means structures were done by inserting genetic algorithm operators and tuning the population. …”
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    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

    Published 2017
    Subjects: “…Evolutionary programming (Computer science). Genetic algorithms…”
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    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    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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    A genetic algorithm optimized RNN-LSTM model for remaining useful life prediction of turbofan engine by Chui, K.T., Gupta, B.B., Vasant, P.

    Published 2021
    “…The weights to combine RNN and LSTM were designed by non-dominated sorting genetic algorithm II (NSGA-II). It achieved average RMSE of 17.2. …”
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    Multilocal feature selection using genetic algorithm for face identification by Mohamad, Dzulkifli

    Published 2008
    “…This paper presents an improved offline face recognition algorithm based on a multi-local feature selection approach for grayscale images. …”
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    Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim by Mohamed Hatim, Shahirah

    Published 2016
    “…The data undergo the pre-processed phase which consists of edge detection, adaptive thresholding segmentation and MATLAB regionprops function for feature extraction. The main goal of the research is to apply the concept of Genetic Algorithm (GA) that can classify hand movements as unlawful behavior in videos. …”
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    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

    Published 2017
    “…Neuro-Fuzzy system (NFS) which is known with its prediction performance has the difficulty in determining the proper number of rules and the number of membership functions for each rule. An enhanced hybrid Genetic Algorithm based Fuzzy Bayesian classifier (GA-FBC) was proposed to help the NFS in the rule extraction. …”
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    Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals by Ahmad, Farzana Kabir, Al-Qammaz, Abdullah Yousef Awwad, Yusof, Yuhanis

    Published 2016
    “…Meanwhile, Genetic Algorithm (GA) and Least squares support vector machine (LS-SVM) have been used as a feature selection technique and classifier respectively.This computational model is tested on the common DEAP pre-processed EEG dataset in order to classify three levels of valence and arousal.The empirical results have shown that the proposed GA-LSSVM, has improved the classification results to 49.22% and 54.83% for valence and arousal respectively, whereas is it observed that 46.33% of valence and 48.30% of arousal classification were achieved when no feature selection technique is applied on the identical classifier.…”
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    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…Instead of selecting features, the proposed algorithm employs a feature scaling system to scale the importance of each band by using Genetic Algorithm (GA) altogether with Extreme Learning Machine (ELM) as classifier, with 1 signifying the most important bands, declining until 0 for the unused bands, as opposed to the 1 and 0 selection system used in BPSO-CSP. …”
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