Search Results - (( using normalization max algorithm ) OR ( java optimization sensor algorithm ))

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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Maximum 2-satisfiability in radial basis function neural network by Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor

“…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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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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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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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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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

“…Wireless sensor networks operate through commonly self-organized sensor nodes to transfer data in a multi-hop approach to a central sink. …”
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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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Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

“…Wireless sensor networks operate through commonly self-organized sensor nodes to transfer data in a multi-hop approach to a central sink. …”
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The Impact of Normalization Techniques on Performance Backpropagation Networks by Norlida, Hassan

“…The normalization techniques used in the experiments are Min-Max, Z-Score, Decimal Scaling, Sigmoidal, and Softmax or Logistic technique. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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MiMaLo: advanced normalization method for mobile malware detection by Sriyanto, Sahib @ Sahibuddin, Shahrin, Abdollah, Mohd Faizal, Suryana, Nanna, Suhendra, Adang

“…MiMaLo is a method to normalize a dataset the usage of the min-max aggregate and logarithm function. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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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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The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems by Atomi, Walid Hasen

“…Specifically Min-Max, Z-Score and Decimal Scaling Normalization preprocessing techniques were evaluated. …”
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Automated characterization of fatty liver disease and cirrhosis using curvelet transform and entropy features extracted from ultrasound images by Acharya, U.R., Raghavendra, U., Fujita, H., Hagiwara, Y., Koh, J.E.W., Jen Hong, T., Sudarshan, V.K., Vijayananthan, A., Yeong, C.H., Gudigar, A., Ng, K.H.

“…Several non-invasive computer-aided techniques are proposed to assist in the early detection of FLD and cirrhosis using ultrasound images. In this work, we are proposing an algorithm to discriminate automatically the normal, FLD and cirrhosis ultrasound images using curvelet transform (CT) method. …”
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Face anti-spoofing using Convolutional Neural Networks / Siti Nurul Izzah Bahrain by Bahrain, Siti Nurul Izzah

“…In this project, the Convolutional Neural Network (CNN) algorithm was implemented using TensorFlow in Python to detect fake face images. …”
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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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Automated diagnosis of diabetes using entropies and diabetic index by Acharya, U.R., Fujita, H., Bhat, S., Koh, J.E.W., Adam, M., Ghista, D.N., Sudarshan, V.K., Chua, K.P., Chua, K.C., Molinari, F., Ng, E.Y.K., Tan, R.S.

“…These redundant features are eliminated by using six feature selection algorithms: Student's t-test, Receiver Operating Characteristic Curve (ROC), Wilcoxon signed-rank test, Bhattacharyya distance, Information entropy and Fuzzy Max-Relevance and Min-Redundancy (MRMR). …”
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DC Motor Control using Ant Colony Optimization by Amr Mansour, Sara

“…It's manufactured by the German company FAULHABER to help the disabled who lost a limb perform their daily activities normally. The motor used in this prosthetic leg is also manufactured by FAULHABER and it's a micro-motor to be light and reliable.…”
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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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