Search Results - (( normal optimization means algorithm ) OR ( variable extractions path algorithm ))

A Stochastic Total Least Squares Solution of Adaptive Filtering Problem by Javed, Shazia, Ahmad, Noor Atinah

“…The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. …”
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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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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

“…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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Cycle time minimization in production line using robust hybrid optimization algorithm by Noorazliza, Sulaiman, Zetty Ain, Kamaruzzaman, Junita, Mohamad Saleh, Ahmad Afif, Ahmarofi

“…As example, memetic algorithm, EGSJAABC3 is applied for economic environmental dispatch (EED) optimization, Hybrid Pareto Grey Wolf Optimization to minimize emission of noise and carbon in U-shaped robotic assembly line and Polar Bear Optimization to optimize heat production. …”
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…Post-optimization ANN model was trained using eleven different leaning algorithms. …”

Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. …”
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Digital filtering optimization on noisy human speech in assistive listening system by Devarajan, Rajasegaran

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A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system by Guichi, Amar, Talha, Abdelaziz, Berkouk, El Madjid, Mekhilef, Saad, Gassab, Samir

“…This technique is based on the combination of two algorithms, the particle swarm optimization algorithm for tracking the global maximum power point, while a newly developed algorithm is used for attaining any other supervisory control set point. …”
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Breast cancer diagnosis through an optimization-driven multispectral gamma correction (ODMGC) by Raj A, Arul Edwin, Ahmad, Nabihah, Durai S, Ananiah

“…The Optimization-Driven Multispectral Gamma Correction (ODMGC) algorithm overcomes challenges in gathering subtle information and detecting cancer in dense breast thermograms. …”
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Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.] by Mahabob, Noratikah Zawani, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

“…As a part of on-going research in classifying the agarwood oil quality, this research presented the optimization of the Multilayer Perceptron (MLP) network with the three different training data network algorithms; Scaled-Conjugate Gradient (SCG), Levenberg Marquardt (LM), and Resilient-Backpropagation (RBP). …”
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Optimized adaptive neuro-fuzzy inference system using metaheuristic algorithms: Application of shield tunnelling ground surface settlement prediction by Liu, Xinni, Hussein, Sadaam Hadee, Kamarul Hawari, Ghazali, Tung, Tran Minh, Yaseen, Zaher Mundher

“…The predictive models were various nature-inspired frameworks, such as differential evolution (DE), particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimizer (ACO) to tune the adaptive neuro-fuzzy inference system (ANFIS). …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

“…The root mean square error is used to compare the performance of the algorithms. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

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A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

“…The objective is to compare various data normalization techniques, including Min-Max Normalization and Z-Score Normalization. …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems by Nik Mohd Zaitul Akmal, Mustapha, Mohd Ashraf, Ahmad

“…For the TRS, the N-SPSA improved the mean objective function by 18.09 % compared to the average multi-verse optimizer sine-cosine algorithm (AMVO-SCA) and 3.42 % compared to the norm-limited (NL-SPSA), while reducing the computational load by 60 % compared to the AMVO-SCA. …”
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Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation by Zaini, Farah Anishah

“…The LSSVM-IBFOA model demonstrates superior performance compared to standalone LSSVM and LSSVM-BFOA based on Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Normalized RMSE (NRMSE), and Determination Coefficient (R²). …”
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Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

“…I used different types of optimization algorithms to improve the performance of the neural networks. …”
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