Search Results - (( wave optimization means algorithm ) OR ( pattern extraction max algorithm ))

A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

Automatic spinal deformity detection based on neural network by Kim, Hyoungseop, Ishikawa, Seiji, Khalid, Marzuki, Otsuka, Yoshinori, Shimizu, Hisashi, Nakada, Yasuhiro, Shinomiya, Takasi, Viergever, Max A.

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A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

“…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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Interferometric array planning using division algorithm for radio astronomy applications by Kiehbadroudinezhad, Shahideh

“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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Hydraulic characterization of PVC-O pipes by means of transient tests by Ghazali, M. F., Nizwan, Che Ku Eddy, Ismail, Nurazima, Sani, M. S.M., Yusof, Mohd Fadhlan M., Mohamed, Zamri

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Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Optimization of flood inundation simulation using multi-resolution Digital elevation model by Abdul Kadir, Muhammad Azraie

“…This is due to the limitation of diffusive wave algorithm, 2-dimensional model and effect of grid configuration. …”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

“…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

“…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. …”
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Triple nonlinear hyperbolic PID with static friction compensation for precise positioning of a servo pneumatic actuator by Abdullah, Lokman, Kamaludin, Khairun Najmi, Syed Salim, Syed Najib, Rafan, Nur Aidawaty, Jamaludin, Zamberi, Rahmat, Mohd Fua'ad, Ramanathan, Rprakash

“…Although the FSS model caters to friction compensation, optimizing the FSS parameter by applying artificial intelligence, such as Neural Networks (NN) and Genetic Algorithm (GA), will increase the friction modeling‘s accuracy, and improve the compensation…”
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Fractal coding of bio-metric image for face authentication by Ahadullah, Md

“…Fractal objects have patterns, convergence, determinism, and reduction in dimensionality. …”
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