Search Results - (( model mitigating means algorithm ) OR ( style classification system algorithm ))

Hybrid genetic random forest algorithm for the identification of ISI-indexed articles / Mohammadreza Moohebat by Mohammadreza, Moohebat

“…After ensuring that the classification technique was able to accomplish this work, Hybrid Genetic Random Forests (HGRF) was introduced as a new ensemble classifier based on a Random Forest algorithm, but altered slightly with some innovations. …”
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Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda by Mohamad @ Hamza, Mohd. Azwan

“…MMB Technique only required a small size of training data. (3) Prediction process of writing style using Multiple Linear Regression (MLR) Algorithm. …”
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Converged Classification Network For Matching Cost Computation by Hamid, Mohd Saad, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan

“…Overall quantitative results for the proposed work performed competitively compared to other established stereo matching algorithm based on the Middlebury standard benchmark online system.…”
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GEOSPATIAL TEMPORAL FRAMEWORK ON LANDSLIDES MITIGATION STRATEGIES FOR PIPELINES by IBRAHIM, MUHAMMAD BELLO

“…AUC values of 0.879 were obtained for the susceptibility models developed from the SVM algorithms, indicating outstanding predictive performance.…”
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A new soft computing model for daily streamflow forecasting by Sammen S.S., Ehteram M., Abba S.I., Abdulkadir R.A., Ahmed A.N., El-Shafie A.

Isolated digit speech recognition in Malay language using Neuro-Fuzzy approach by Sabah, R., Ainon, R.N.

“…To recognize the Malay speech digits, the endpoint detection algorithm is used to trim the silent duration in speech sample, the Mel Frequency Cepstral Coefficient technique is used to extract speech features, the subtractive clustering algorithm is applied to identify the fuzzy inference system, and the Adaptive Neuro Fuzzy Inference System (ANFIS) is used as a modern classification technique to train in identifying the features of speech. …”
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Performances analysis of heart disease dataset using different data mining classifications by Wan Zunaidi, Wan Hajarul Asikin, Saedudin, RD Rohmat, Ali Shah, Zuraini, Kasim, Shahreen, Sen, Seah Choon, Abdurohman, Maman

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Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity by Ghasemi, Sepehr, Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

“…The dominant saturation nonlinearity is in the transducers, which can be represented by a Wiener model. An effective solution to mitigate such nonlinear distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. …”
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Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity by Dehkordi, Sepehr Ghasemi

“…The dominant saturation nonlinearity in the transducers is the loudspeaker which can be represented by a Wiener model. An effective solution to mitigate such nonlinearly distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. …”
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CHINESE CHARACTER RECOGNITION USING SUPPORT VECTOR MACHINE by Baharum A., Ismail R., Wahab S.H.A., Deris F.D., Noor N.A.M., Kasihmuddin M.S.M.

“…Support vector machines are a classification of two classes widely used in classification. …”

SpickME: Choosing spectacles prediction system by using multinomial Naïve Bayes / Nurul Nabilah Johari by Johari, Nurul Nabilah

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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Mean Squared Error (MSE) shows that the Random Forest model makes more accurate predictions than the others. …”
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Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of kelantan river in malaysia by Hayder G., Solihin M.I., Mustafa H.M.

“…Additionally, the developed nonlinear multivariable regression model using CFNNPSO produced acceptable prediction accuracy during model testing with the regression coefficient (R2), root mean square error (RMSE), and mean of percentage error (MPE) of 0.88, 191.1 cms and 0.09%, respectively. …”

Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

“…Distinctive system gaining knowledge of strategies are systematically examined on numerous databases.…”
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Short-term PV power forecasting using hybrid GASVM technique by VanDeventer, William, Jamei, Elmira, Thirunavukkarasu, Gokul Sidarth, Seyedmahmoudian, Mehdi, Tey, Kok Soon, Horan, Ben, Mekhilef, Saad, Stojcevski, Alex

“…The forecasting accuracy of the proposed GASVM model is evaluated based on the root mean square error (RMSE) and mean absolute percentage error (MAPE). …”
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Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexing for optical fiber transmission by Noori, Awab

“…However, the existing MDM equalization algorithms can only mitigate the linear distortion, but they cannot address nonlinear distortion in the signal accurately. …”
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Evaluation of Instagram's neural machine translation for literary texts: an MQM-Based Analysis by Fakih, Altaf, Ghassemiazghandi, Mozhgan, Fakih, Abdul-Hafeed, Manjet K. M. Singh

“…The findings suggest a need for enhanced algorithms and linguistic architecture in Neural Machine Translation systems to better recognize linguistic variants and text genres for more accurate and fluent translations.…”
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