Search Results - (( java applications tree algorithm ) OR ( parameter implementation max algorithm ))
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…In this work, two AP selection algorithms are proposed which are Max Kernel and Kernel Logistic Discriminant that implement the knowledge of kernel density estimate and logistic regression machine learning classification. …”
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Thesis -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Article -
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. …”
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Vertical Handover Decision Processes for Fourth Generation Heterogeneous Wireless Networks
Published 2013“…The survey revealed that the currently proposed VHD algorithms either lacked a comprehensive consideration of several network parameters or studies’ reporting these problems lacks sufficient detail for implementation.…”
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Ant colony optimization in dynamic environments
Published 2010“…The last objective of this thesis is to optimize the parameter settings of the best performing ant algorithm with local search. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Embedded Artificial Intelligent (AI) To Navigate Cart Follower
Published 2018“…The set of parameters used in traingd are lr, max_fail, min_grad, goal, time, and epochs. …”
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Monograph -
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…We demonstrate that with optimal parameters selected for sparsity of feature maps, the pooling operation (here max pooling) when used layered wise in ML-CSC framework improves the effective dictionaries and resulting feature maps, which in turn improves the reconstruction accuracy of images after multilayered implementation.…”
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Proceeding Paper -
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Conference or Workshop Item -
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Robust PID anti-swing control of automatic gantry crane based on Kharitonov's stability
Published 2009“…The proposed method employs Genetic Algorithm (GA) in min-max optimization to find the stable robust PID. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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An intelligent network selection mechanism for vertical handover decision in vehicular Ad Hoc wireless networks
Published 2020“…This study uses a network simulator (NS-2) as the mobility traffic network and vehicular mobility traffic (VANETMobiSim) generator to implement a topology in a realistic VANET mobility scenario in Wi-Fi, WiMAX, and LTE networks technologies. …”
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