Search Results - (( java adaptation optimization algorithm ) OR ( pattern generation max algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Deterministic Automatic Test Pattern Generation for Built-In Self Test System by Mohammed Khalid, Muhammad Nazir

“…The test pattern generation can be generated either manually or automatically. …”
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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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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…The dataset used for analyzing stock prices often displays complex patterns and high volatility, making the generation of accurate predictions difficult. …”
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Embedded Artificial Intelligent (AI) To Navigate Cart Follower by Tang, Khai Luen

“…The weights and biases generated through the training process is depended on the training algorithm, initial weights and biases for training and the dataset used in the process. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…The Min-Max, Z-Score, and Decimal Scaling Normalization pre-processing techniques were analyzed. …”
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A scene invariant convolutional neural network for visual crowd counting using fast-lane and sample selective methods by Teoh, Shen Khang

“…The proposed model is designed with single column architecture using single filter size and max pooling size. Fast lane connection and sample selective algorithms have been designed specifically to tackle the issue of vanishing gradient and enhance the quality of the model. …”
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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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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Fractal coding of bio-metric image for face authentication by Ahadullah, Md

“…The thesis also compares the results of enough images of various sizes generated by the proposed algorithms with the results of other fractal coding methods to confirm the algorithms’ clarity, reliability and validity. …”
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