Search Results - (( parameter organization learning algorithm ) OR ( code classification mining algorithm ))
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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Classification of metamorphic virus using n-grams signatures
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach
Published 2018“…Recent advances in machine learning have allowed us to quantify the parameters that are important for the fabrication of high efficient phosphorescent bottom emitting organic light emitting diodes (PhOLEDs). …”
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Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.]
Published 2021“…This parameter estimates the biodegradable organic matter present in the water. …”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures
Published 2024“…The algorithm’s distinctive feature lies in its ability to perform non-numeric computations, rendering it adaptable to intricate deep learning problems. …”
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Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah
Published 2015“…In this thesis, the issues of concern include assigning the limited resources of Physical Cell Identity (PCI) for the high number of deployed femtocells, to ensure network collision and confusion free after deploying the PCI, determine the exact geographic location of femtocell, and identifying the learning parameters for the optimized self—organizing handover process for LTE femtocell-based networks. …”
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Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale
Published 2021“…A machine learning is needed to predict the contact angle in the shale using the process parameters and TOC and Minerology of the shale. …”
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Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure
Published 2004“…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. …”
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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification
Published 2010“…Growing self-organizing map (GSOM) has been introduced as an improvement to the self-organizing map (SOM) algorithm in clustering and knowledge discovery. …”
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An enhanced android botnet detection approach using feature refinement
Published 2019“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework
Published 2024“…In this project, the machine learning (ML) framework with different algorithm models and kernel functions was employed to predict the device performance of solution-processed SnO2-based organic solar cells. …”
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Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia
Published 2023“…Agricultural robots; Ammonia; Forecasting; Lakes; Learning algorithms; Machine learning; Motion estimation; Multilayer neural networks; Rivers; Sensitivity analysis; Water quality; Agricultural activities; Health condition; Movement control; Multi layer perceptron; Reconnaissance surveys; Three parameters; Water quality indexes; World Health Organization; Quality control; COVID-19; lake water; river water; spatiotemporal analysis; surface water; water quality; World Health Organization; Malaysia; Penang; Putrajaya; Putrajaya Lake; West Malaysia…”
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