Search Results - adoption model different ((estimation algorithm) OR (encryption algorithm))

A new KD-3D-CA block cipher with dynamic S boxes based on 3D cellular automata by Hamdi, Ayman Majid

“…Lastly, KD-3D-CA Block cipher is more complex and it outperforms AES with more than 25% for different key sizes. Deductively, the proposed KD-3D-CA block cipher algorithm is more secure than other block cipher algorithms and can be implemented for data encryption and decryption.…”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Firstly, the study concludes that the adoptions of the flexible approach in estimation can model the binary feature of CVDs and non-linear paths in the complex path models. …”
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Apply and optimize machine learning algorithms for estimating battery health by Chin, Wai Yee

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Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises by Suparman, Suparman, Abdellah Salhi, Abdellah Salhi, Rusiman, Mohd Saifullah

“…After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

“…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…The best MR model is model M52.5.5 Newton, however, the best PR model (P57.14.6 Newton) is found to give an improved estimation. …”
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Environmental factors and spatial heterogeneity affect occupancy estimates of waterbirds in Peninsular Malaysia by Chukwuemeka, Onwuka Martins, Oluwatobi, Emmanuel Olaniyi, Hussin, Mohamed Zakaria

“…The automatic linear modelling algorithm results for PIW waterbirds also showed that the maximum and minimum weights of the factors were land cover and water dissolved oxygen, while in PW they were atmospheric pressure and Normalized Difference Water Index (NDWI). …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…Bubble size distribution which is regarded as the most important characteristics of froth structure, is being addressed in this thesis by using a segmentation algorithm. A marker based watershed algorithm had been adopted and improved so as to prevent the over segmentation of big bubbles and able to adapt itself with different scenario of froth images. …”
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Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal by Mohd Fadhlan, Mohd Yusof

“…However, the ANN model recorded a more accurate and precise estimation with the lowest estimation error, i.e., 3.3%. …”
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River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

“…Although the proposed model could be applied in different case study, there is a need to tune the model internal parameters when applied in different case study. � 2022, The Author(s).…”

Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…DASC-FS integrates the Adaptive Sine Cosine Algorithm (ASCA) as a search algorithm to determine the relevant features and adopts Depth Linear Discriminant Analysis (D-LDA) to identify the discriminative features that maximize class sepa ration. …”
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A new correlation for oil formation volume factor of oil and gas mixture using Group Method of Data Handling; an empirical approach by Elhadi Eljezooly, Ahmad Azhari

“…The performance of GMDH model is compared against the best correlating adopted by the industry currently. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

“…Data-driven models for predicting fire and explosion-related properties have been improved greatly in recent years using machine-learning algorithms. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The Random Tree standalone ML-AP relay model presented the best performing models from the ML-APS relay model with the best average performance for the correctly classified fault types of 97.61 % at 5 % significance level above other ML algorithms. …”
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Comparison between regression and ANN models for relationship of soil properties and electrical resistivity by Siddiqui, F.I., Pathan, D.M., Osman, S.B.A.B.S., Pinjaro, M.A., Memon, S.

“…The regression models of relationship between electrical resistivity and various soil properties used in the current research for the purpose of comparison with artificial neural network (ANN) models were adopted from the work of Siddiqui and Osman (Environ Earth Sci 70:259â��26, 2013). …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…Unlike traditional methods that usually start with detection and followed by denoising, the model initially leverages the powerful ability of deep CNN architecture to separate noise from noisy image, then adopts PSO to pinpoint the most optimized threshold values for detecting impulse noisy pixels. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. …”
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