Search Results - (( java application optimisation algorithm ) OR ( mixed methods learning algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Sentiment Analysis on Mixed-Language Social Media Post by Mohamed Salleh F.H., Gorment N.Z., Mohd Ridza M.H.

“…Several machine learning algorithms were identified and trained to classify a Manglish post as either positive or negative. …”

Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations by Goheannee

“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Hybrid performance measures and mixed evaluation method for data classification problems by Hossin, Mohammad

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Removing mixture of Gaussian and Impulse noise of images using sparse coding by Mahsa Malekzadeh, Saeed Meshgini, Reza Afrouzian, Ali Farzamnia, Sobhan Sheykhivand

“…Many mixed noise removal methods are based on a detection method that generates artificial products in case of high noise levels. …”
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A comparative study of vibrational response based impact force localization and quantification using different types of neural networks / Wang Yanru by Wang, Yanru

“…In addition, ANFIS uses hybrid learning algorithm. It is mixed with least mean square and gradient descent method, which cause many advantages, such as much better learning ability and less computational time. …”
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Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

“…However, traditional machine learning and image processing methods used handcrafted feature extraction methods. …”
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A review article on software effort estimation in agile methodology by Sudarmaningtyas, Pantjawati, Rozlina, Mohamed

“…The implementation of all machine learning methods used a hybrid approach, which is a combination of machine learning and expert judgement, or a mix of two or more machine learning. …”
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A review article on software effort estimation in agile methodology by Sudarmaningtyas, Pantjawati, Rozlina, Mohamed

“…The implementation of all machine learning methods used a hybrid approach, which is a combination of machine learning and expert judgement, or a mix of two or more machine learning. …”
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Exploring nexus of social media algorithms, content creators, and gender bias: a systematic literature review by Lou, Shijun, Adzharuddin, Nor Azura, Syed Zainudin, Sharifah Sofiah, Omar, Siti Zobidah

“…Abstract: Drawing on the PRISMA framework, this study systematically investigates the dynamics between social media algorithms, content creators, and gender bias. An analysis of 18 quantitative and mixed-method studies from the Web of Science and Scopus databases, spanning 2019 to 2023, uncovers three main research trajectories: algorithms' influence on gender bias, their role in shaping content, and the interactions between algorithms, gender bias, and content creators. …”
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Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model by Mohamad Zamri, Isma Uzayr, Abd Rahman, Mohd Amiruddin, Bundak, Caceja Elyca

“…Furthermore, we compare the accuracy of our PSO-SVR algorithm with other previous studies method such as BSVR, ANN, and linear regression. …”
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Application of machine learning and artificial intelligence in detecting SQL injection attacks by Md Sultan, Abu Bakar, Agiliga, Nwabudike Augustine, Osman, Mohd Hafeez Bin, Sharif, Khaironi Yatim

“…The main aim of this work is focusing on solving the IT-related challenge lack-of-adequate knowledge bases and tools for security practitioners to monitor and mitigate SQL Injection attacks with AI/ML techniques. The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. …”
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CT-eKit: computational thinking interactive learning / Ong Sing Ling, Jill Ling and Fetylyana Nor Pazilah by Ong, Sing Ling, Jill, Ling, Pazilah, Fetylyana Nor

“…A mixed method was employed to investigate the students' learning experience with CT-eKit. …”
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On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay by Aneesha Pillay , Balachandran Pillay

“…A comparative study based on machine learning algorithms was also conducted by using all features and the RFE-selected features to classify the R. rattus sample based on the age groups. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The second algorithm reduces the quantity of interest regions by using the Extremal Region Selection (ERS) algorithm. …”
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Malware detection using machine learning / Nur Wahida Kausar Abd Rahman by Abd Rahman, Nur Wahida Kausar

“…So far, a number of static and dynamic malware classification algorithms have been reported. This study shows how malware families may be classified using a deep learning-based malware detection (DLMD) strategy based on static methodologies. …”
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