Search Results - (( java adaptation optimization algorithm ) OR ( making using normalization algorithm ))

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

An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

“…Based on its simplicity, the K-means algorithm has been used in many fields. This paper proposes improved normalization and standardization techniques for higher purity in K-means clustering experimented with benchmark datasets from UCI machine learning repository and it was found that all the proposed techniques’ performance was much higher compared to the conventional K-means and the three classic transformations, and it is evidently shown by purity and Rand index accuracy results.…”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…In order to make the normal people can cluster their data easily, this project aims is to develop a web-based clustering tool that can be used by all peoples. …”
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Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

“…Before training, the dataset is normalized using the min-max normalization technique to reduce the influence of noise. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”

Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach by Farid, Mazen, Heng, Siong Lim, Chin, Poo Lee, Latip, Rohaya

“…We compare our proposed method to five distinct decision-making procedures using common scientific workflows with competing objectives: Pareto dominance, multi-criteria decision-making (MCDM), linear normalization I, linear normalization II, and weighted aggregated sum product assessment (WASPAS). …”
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Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

“…This algorithm was minimal in line code to make it lightweight and made use of the controller's functionality without adding extra computational burden on the controller.…”
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Analysis of avalanche effect on advance encryption standard by using dynamic S-Box depends on rounds keys by Nejad, Farshid Hossein, Sabah, Saman, Jam, Amid Jamshidi

“…The parameters of the dynamic S-Box have features equivalent to those in the normal algorithm AES. Static S-Box allows attackers to study S-Box and discover weak issues while by using dynamic S-Box approach, it makes difficult and more complex for attacker to do any offline study of an attack of one particular set of S- boxes. …”
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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 findings demonstrate that applying normalization techniques effectively enhances classification performance compared to using unnormalized data. …”
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New approaches to normalization techniques to enhance k-means clustering algorithm by Dalatu, Paul Inuwa, Midi, Habshah

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Smart diagnosis of long bone tumor / Mazni Parimin by Parimin, Mazni

“…Here, backpropagation training algorithm will be used and network parameters will be set. …”
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The Impact of Normalization Techniques on Performance Backpropagation Networks by Norlida, Hassan

“…This study explored several normalization techniques using backpropagation learning. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. Every algorithm makes its own respective prior assumptions about the relationships between the features and target variables, which create different types and levels of bias. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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An improved image steganography algorithm based on PVD by Bhuiyan, Sharif Shah Newaj, Abdul Malek, Norun, Khalifa, Othman Omran, Abdul Rahman, Farah Diyana

“…In this paper, a modification of PVD (Pixel Value Differencing) algorithm is used for Image Steganography in spatial domain. …”
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Stroke-to-stroke matching in on-line signature verification by Ahmad Jaini, Azhar

“…The aim of this research is to develop a new approach to map the strokes in both test and reference signatures as well as to verify the originality of the test signatures. Current methods make use of the DTW algorithm and its variant to segment them before comparing each of its data dimension. …”
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Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

“…Nevertheless, in real situations, many estimates are not normal and the use of bootstrap method is more appropriate as it does not rely on the normality assumption. …”
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Adaptive interference canceller using analog algorithm with offset voltage by Mohammed, Alaa Hadi

“…The experimental tests of the proposed algorithm have shown that the reduction percentage in the MSE output using the proposed algorithm is 51% compared to the NLMS algorithm and 61% compared to the RLS algorithm. …”
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Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

“…The fuzzy clustering process are made using three algorithms : Fuzzy C-Means (FCM), Gustafsof-Kessel (GK) and Gath-Geva (GG) algorithm. …”
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