Search Results - (( developing effective traits algorithm ) OR ( java implication based algorithm ))
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1
Tag clouds algorithm with the inclusion of personality traits
Published 2015“…The algorithm was developed based on three theories of personality traits, namely Myers-Briggs Type Indicator (MBTI), Shape, and Multiple Intelligence (MI). …”
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Personalized Recommendation Classification Model of Students’ Social Well-being Based on Personality Trait Determinants Using Machine Learning Algorithms
Published 2023“…This study classifies the effects of the Big 5 Personality Traits (Extraversion, Openness, Agreeableness, Emotional Stability, and Conscientiousness) on students’ Industry 4.0 Social Well-being levels by analyzing their demographic and personality traits. …”
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Making programmer effective for software development teams: An extended study
Published 2017“…It was found that extrovert (E) trait programmers can be suitable with E trait team-leaders. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan
Published 2023“…The project follows a modified waterfall approach, focusing on creating a user-friendly interface and integrating the Random Forest Classification Algorithm for accurate detection. The results show the algorithm's impressive performance with an 86% precision in predicting ASD traits. …”
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Development of submergence tolerant rice variety through marker-assisted backcross breeding between MR219 and Swarna-Sub1
Published 2015“…Marker-assisted selection (MAS) is an effective approach than the conventional breeding for rice varietal development. …”
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…Therefore, many researchers have applied and developed various machine learning algorithms that could efficiently tackle the handwritten digit recognition problem. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…Each quadrant provides five rice biomass traits during the tillering, booting, and milking stages. …”
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Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review
Published 2022“…The research and practices reported in the study also show how personalized learning was used and factors that made it work, thus the finding of this paper will guide other researchers to recognize various personal traits and the identification of appropriate technology trends and activities for further studies, as well as assist developers in the development of the personalized learning system and closely related to the adaptive learning systems.…”
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In silico approaches for unearthing bacterial quorum-sensing inhibitors against pathogenic bacteria
Published 2019“…Thus, certain group of researchers also developed machine learning tools based on support vector machine (SVM) and hidden Markov models (HMM) for the identification of novel and effective biofilm inhibitory peptides (BIPs), while others used in silico approaches for predicting and designing of antibiofilm peptides usingbidirectional recursive neural network (BRNN) and Random Forest (RF) algorithms. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration
Published 2022“…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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Ranking-based pruning and weighted support model for gene association in frequent itemsets / Sofianita Mutalib
Published 2019“…But many of the variants and its effect remain a mystery which has high potential of knowledge discovery especially for complex diseases. …”
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Self-Organized Wireless Sensor Network (SOWSN) for dense jungle applications
Published 2023“…In this paper, we introduce the SelfOrganized Wireless Sensor Network (SOWSN) to overcome these challenges. To develop the traits needed for such SOWSN nodes, three types of computational intelligence mechanisms have been featured in the design. …”
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