Search Results - (( developing voting process algorithm ) OR ( java application tree algorithm ))
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Secure E-Voting With Blind Signature
Published 2003“…We have developed an electronic voting system, E-Voting for a general election. …”
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Conference or Workshop Item -
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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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Mining Sequential Patterns using I-PrefixSpan
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TOPSIS-based Regression Algorithms Evaluation
Published 2022“…The developed approach established the weights, which were the core of the evaluation process, to various values to mimic and address the regression’s utilization in multiple applications with different concerns and using distinct datasets. …”
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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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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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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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Hotel recommendation system using machine learning
Published 2025“…The future work includes expanding the dataset, refining the recommendation algorithm, using natural language processing techniques with the addition of multilingual reviews, and deploying the system as a user-friendly application or mobile application.…”
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Final Year Project / Dissertation / Thesis -
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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Distance measure and its application to decision making, medical diagnosis, and pattern recognition problems under complex picture fuzzy sets
Published 2025“…Finally, we developed an algorithm using complex picture fuzzy environments and applied it to a practical application concerning decision making, medical diagnosis, and pattern recognition problems. ? …”
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Pre-processing strategies for skin detection using MLP
Published 2011“…These features will be used as inputs to the MLP classifiers. A modified Growing algorithm for finding the number of neurons in the hidden layer of a neural network was also developed it was able to reduce the computational time compared to the conventional Growing algorithm. …”
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Augmenting the Robustness and Efficiency of Violence Detection Systems for Surveillance and Non-Surveillance Scenarios
Published 2022“…EvoKeyNet utilizes an evolutionary algorithm to select optimal feature attributes, while KFCRNet employs an ensemble of LSTM, Bi-LSTM, and GRU models with a voting scheme. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization
Published 2023“…Data from an academic institution were collected and pre-processed by encoding relevant features before applying various machine learning predictive models. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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