Search Results - (( user evaluation method algorithm ) OR ( feature selection method algorithm ))
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An ensemble feature selection method to detect web spam
Published 2018“…An ensemble feature selection method has been proposed in this paper to detect web spam. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…However, the developed algorithms only consider the selected features from a peak model based on the understanding of the EEG signals characteristics. …”
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Comparison on machine learning algorithm to fast detection of malicious web pages
Published 2021“…Compared to several decision tree method, Random Forest has shown promising and higher sensitivity result towards malicious data which is 98.3% compared to other classification algorithm…”
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A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Tag cloud algorithm with the inclusion of personality traits
Published 2014“…Therefore, the main objective of this study is to make tag cloud algorithm with the inclusion of personality traits by adjusting two prominent visual features (color and shape) as an integration of layout.In addition, the utilization of RBS (rule bas e system) approach as artificial intelligent method is also taken into account to make knowledge base that stores the relationship between the proper personality elements and particular layout.This paper also discusses findings from satisfaction evaluation of prototyping, which comprises three dimensions facet: overall layout, color, and shape .The findings showed that the majority mean value for each dimension is categorized in agree scale (6-point), which indicates that respondents are satisfied with the tag cloud layout display generated by proposed algorithm.The findings suggest interface designers to be careful in selecting the appropriate tag clouds layout to be displayed for users with varying personality differences.…”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. Then, these tissues are classified into tumors and blood vessels by an AdaBoost classification method based on tissue features extracted utilizing first, second and higher order image features selected by a minimal-redundancy maximalrelevance feature selection approach. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony
Published 2022“…In this project, a comparative evaluation of selected algorithms is done to ascertain their applicability, practicality, and adaptability in a cloud scenario. …”
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Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language
Published 2016“…Thus by adding processes before classification methods such as feature selection methods can provide better data input in the classification process, it is expected to improve the performance of the method of classification. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…For algorithm performance evaluation, the ML-IDS is compared with ML-CICIDS-59 and ML-CICIDS-45, which are IDS trained using the CICIDS-2018 dataset after performing feature engineering. …”
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Document ranking using information quality criteria in weblog search engine
Published 2013“…Thus, the use of traditional rank algorithms like PageRank and HITS in general search engines are not appropriate to evaluate the Weblog posts because such algorithms do not consider the blog specific features. …”
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A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent
Published 2023“…Hence, a feature selection method is necessary to pick the right features. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm
Published 2024“…Afterward, a mathematical version is used to symbolize the layout preference problems, and the layout scheme selection method is simulated. In the give-up, the advised model’s viability is checked by means of looking at how fixtures from the product’s layout picks had been carried out to assist designers give us fresh thoughts.…”
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Development of a systematic method in lean tool selection for automotive industry
Published 2012“…The current research paves the path to propose a generalized method that makes it possible for a user to holistically recognize and evaluate the tools influencing the application of lean manufacturing developments. …”
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Improving intelligent personality prediction using Myers-Briggs type indicator and random forest classifier
Published 2020“…Researchers compared the performance of the proposed method in this study with other popular machine learning algorithms. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao
Published 2024“…Utilizing the Shapley Additive Explanations interpretation method, the analysis emphasized the importance of selected features in predicting wood acoustic quality, highlighting "Spectral Roll-off 85%" as the most crucial predictor of sound quality. …”
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB)
Published 2017“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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