Search Results - (( developing estimation machine algorithm ) OR ( java application designing algorithm ))

Software project estimation with machine learning by Zakaria, Noor Azura, Ismail, Amelia Ritahani, Yakath Ali, Afrujaan, Mohd Khalid, Nur Hidayah, Zainal Abidin, Nadzurah

“…This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Estimation of electric vehicle turning radius through machine learning for roundabout cornering by Ashaa, Supramaniam, Muhammad Aizzat, Zakaria, Kunjunni, Baarath, Mohamad Heerwan, Peeie, Ahmad Fakhri, Ab. Nasir, Muhammad Izhar, Ishak

“…The feasibility of the developed algorithm was tested and validated using performance metrics. …”
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Software effort estimation using machine learning technique by Rahman, Mizanur, Roy, Partha Protim, Ali, Mohammad, Gonçalves, Teresa, Sarwar, Hasan

“…In order to better effectively evaluate predictions, this study recommends various machine learning algorithms for estimating, including k-nearest neighbor regression, support vector regression, and decision trees. …”
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A review article on software effort estimation in agile methodology by Sudarmaningtyas, Pantjawati, Rozlina, Mohamed

“…The results showed the top three estimation that is applied in Agile, are machine learning (37%), Expert Judgement (26%), and Algorithmic (21%). …”
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A review article on software effort estimation in agile methodology by Sudarmaningtyas, Pantjawati, Rozlina, Mohamed

“…The results showed the top three estimation that is applied in Agile, are machine learning (37%), Expert Judgement (26%), and Algorithmic (21%). …”
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Sensorless control system for assistive robotic ankle-foot by Al Kouzbary, Mouaz, Abu Osman, Noor Azuan, Wahab, Ahmad Khairi Abdul

“…This article presents a novel sensorless control system of assistive robotic ankle-foot prosthesis, two estimation algorithms were developed and an analogy between them has been made. …”
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Redundancy allocation for a high security control system using estimation of distribution algorithm by Melo, Haydee, Watada, Junzo, Prof.

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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

“…Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms which are one of the challenging issues in the agricultural sector. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”

Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian by Ng, Tarng Jian

“…The study addresses challenges posed by signal fluctuations, non-line-of-sight propagation, and the need for continuous positioning estimation in dynamic environments. Through experimental evaluation and comparison of various machine learning algorithms, including Deep Gaussian Process (DGP) regression, the research demonstrates the effectiveness of DGPs in achieving precise single-point estimation, by keeping the mean absolute error to below 5 meters. …”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

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Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm by Al Hazza, Muataz, Adesta, Erry Yulian Triblas, Superianto, M. Y., Riza, Muhammad

“…Thus, developing a model for estimating the cutting parameters and optimizing this model to minimize the cutting temperatures and surface roughness becomes utmost important to avoid any damage to the quality surface.This paper presents the development of new models and optimizing these models of machining parameters to minimize the cutting temperature in end milling process by integrating the genetic algorithm (GA) with the statistical approach. …”
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Improving forest above-ground biomass estimation by integrating individual machine learning models by Luo, Mi, Ahmad Anees, Shoaib, Huang, Qiuyan, Qin, Xin, Qin, Zhihao, Fan, Jianlong, Han, Guangping, Zhang, Liguo, Mohd Shafri, Helmi Zulhaidi

“…Machine learning algorithms have been proven to have great potential in forest AGB estimation with remote sensing data. …”
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