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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…However, the MGCACO algorithm has three main drawbacks in producing a features subset because of its clustering method, parameter sensitivity, and the final subset determination. …”
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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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A model for gene selection and classification of gene expression data by Mohamad, Mohd Saberi, Omatu, Sigeru, Deris, Safaai, Mohd Hashim, Siti Zaiton

“…One problem arising from these data is how to select a small subset of genes from thousands of genes and a few samples that are inherently noisy. …”
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Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification by Mohamad, Mohd. Saberi, Deris, Safaai, Hashim, Siti Zaiton Mohd.

“…This work deals with finding the small subset of informative genes from gene expression microarray data which maximize the classification accuracy. …”
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Neural network-based codebook search for image compression by Bodruzzaman, M., Gupta, R., Karim, M.R., Bodruzzaman, S.

“…The image to be coded is first clustered into a small subset of neighboring images and then the neural network-based encoder is used to find the best matching code sequences in the codebook. …”
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Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Quantitative analysis evaluation of image reconstruction algorithms between digital and analog PET-CT by Chen, Ew-Jun *, Haniff Shazwan, Safwan Selvam, Lee, Hee Siang, Chew, Ming Tsuey *

“…High quality diagnostic images and quantitative accuracy are often restricted by image noise, adequate spatial resolution and contrast ratio. Ordered Subset Expectation Maximisation (OSEM) is a widely used statistical iterative reconstruction algorithm in PET-CT due to its dependability, reconstruction quality and adequate signal-to-noise ratio. …”
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri

“…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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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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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…An agent learns the strategy of selecting a subset of small image regions, which are more knowledgeable than the whole set of images from an unlabeled data pool. …”
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Acquisition of new subscribers using analytical models in the telecommunication industry / Nik Muhammad Naim Nik Ghazali by Nik Ghazali, Nik Muhammad Naim

“…Network quality is used in the model by finding out the maximum number of new subscribers that can be added into a given district without causing any network quality drop to the current customers in the same district. The algorithm is developed for the analytical acquisition model and the result shows that the model managed to achieve the set target mobile revenue with only a small number of subscribers. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
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Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

“…Machine Learning (ML) and Artificial Intelligence (AI) are closely intertwined and represent the latest cutting-edge technologies that facilitate the development of intelligent prototypes. Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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The application of artificial intelligent techniques in oral cancer prognosis based on clinicopathologic and genomic markers / Chang Siow Wee by Chang, Siow Wee

“…AI techniques are good for handling noisy and incomplete data, and significant results can be attained despite small sample size. Various AI techniques have been applied in medical research such as artificial neural networks, fuzzy logic, genetic algorithm and other hybrid methods. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques by Googhari, Shahram Karimi

“…The sudden flow changes in these small tropical catchments resulting in these peak flows are common due to their small areal extent and to the intense localized phenomenon of tropical showers.…”
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