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Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation by Cheah, Kah Wai

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Short term forecasting based on hybrid least squares support vector machines by Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor

“…This study assesses the performance of each hybrid algorithms based on three statistical indices viz. Mean Square Error (MSE), Root Mean Square Percentage Error (RMSPE) and Theil’s U which is realized on raw and normalized data set. …”
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Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

“…Furthermore, the modeling of the THF can be realized using least mean square (LMS) algorithm and utilized in the NLFXLMS control scheme. …”
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A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization by Padmanaban S., Priyadarshi N., Bhaskar M.S., Holm-Nielsen J.B., Ramachandaramurthy V.K., Hossain E.

“…Controllers; Distributed power generation; Electric inverters; Electric power system protection; Fuzzy control; Fuzzy inference; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Inference engines; Maximum power point trackers; Mean square error; Membership functions; Optimization; Photovoltaic cells; Adaptive neuro-fuzzy inference system; Anti-islanding protection; Artificial bee colony algorithms (ABC); Experimental realizations; Experimental validations; Fuzzy-logic control; Photovoltaic systems; Root mean square errors; Electric power system control…”

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. …”
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All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

“…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. The proposed narrowband LMS algorithm would benefit in the design of efficient feedforward ANC system that can realize noise control in air intake duct applications.…”
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Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines by Zuriani, Mustaffa, M. H., Sulaiman

“…Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE). Findings of the study suggested that the GWO-LSSVM possess lower prediction error rate as compared to three comparable algorithms which includes hybridization models of LSSVM and Evolutionary Computation (EC) algorithms.…”
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Hybrid least squares support vector machines for short term predictive analysis by Zuriani, Mustaffa, Ernawan, Ferda, M. H., Sulaiman, Syafiq Fauzi, Kamarulzaman

“…Moth-flame Optimization (MFO) algorithm is a relatively new optimization algorithm which is classified as Swarm Intelligence (SI). …”
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Application of LSSVM by ABC in energy commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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Gasoline price forecasting: An application of LSSVM with improved ABC by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…Optimizing the hyper-parameters of Least Squares Support Vector Machines (LSSVM) is crucial as it will directly influence the predictive power of the algorithm.To tackle such issue, this study proposes an improved Artificial Bee Colony (IABC) algorithm which is based on conventional mutation.The IABC serves as an optimizer for LSSVM.Realized in gasoline price forecasting, the performance is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Percentage Error (RMSPE).The conducted simulation results show that, the proposed IABCLSSVM outperforms the results produced by ABC-LSSVM and also the Back Propagation Neural Network.…”
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Dengue outbreak prediction: hybrid meta-heuristic model by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

“…Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

“…Realized in commodity time series data, the proposed technique is compared against two comparable techniques, including single GWO and LSSVM optimized by Artificial Bee Colony (ABC) algorithm (ABC-LSSVM). …”
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New Evolving Fuzzy System Algorithms Using Dynamic Constraint by Ahme, Md. Manjur

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Forecasting model based on LSSVM and ABC for natural resource commodity by Yusof, Yuhanis, Kamaruddin, Siti Sakira, Husni, Husniza, Ku-Mahamud, Ku Ruhana, Mustaffa, Zuriani

“…Reliable forecast of the price of natural resource commodity is of interest for a wide range of applications.This includes generating macroeconomic projections and in assessing macroeconomic risks.Various approaches have been introduced in developing the required forecasting models.In this paper, a forecasting model based on an optimized Least Squares Support Vector Machine is proposed.The determination of hyper-parameters is performed using a nature inspired algorithm, Artificial Bee Colony.The proposed forecasting model is realized is gold price forecasting.The undertaken experiments showed that the prediction accuracy and Mean Absolute Percentage Error produced by the proposed model is better compared on the one produced using Least Squares Support Vector Machine as an individual.…”
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Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

“…By using the restricted isometry property, the theoretical analysis of both CoFA and SdMP algorithms and the sufficient conditions for realizing an improved reconstruction performance were presented. …”
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RLS channel estimation and tracking for MIMO-extended IEEE 802.11a WLANs by Saeed, Mohammed Abdo, Noordin, Nor Kamariah, Mohd Ali, Borhanuddin, Khatun, Sabira, Ismail, Mahamod

“…In this paper, an adaptive channel estimation and tracking scheme based on recursive least squares (RLS) algorithm is proposed for MIMO OFDM-based wireless local area networks (WLANs). …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

An application of barnacle mating optimizer in infectious disease prediction: a dengue outbreak cases by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Mohamad Farhan, Mohamad Mohsin, Yuhanis, Yusof, Ferda, Ernawan, Bariah, Yusob, Noorhuzaimi, Mohd Noor

“…For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Mean Absolute Deviation (MAD) were employed to validate the performance of the identified algorithms which includes the comparison between BMO against Moth Flame Optimizer (MFO) and Grey Wolf Optimizer (GWO) algorithms. …”
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Design and evaluation of multidimensional turbo product coded MIMO-OFDM system by Muladi, Muladi

“…The final task is designing the accurate channel estimation for the AGSMST- MDTPC-MIMO-OFDM system employing pilot symbol assistance and least square estimation using mean-square error criterion. …”
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