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1
Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…Species Distribution Models (SDMs) are a powerful tool to derive habitat suitability predictions relating species occurrence data with habitat features. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…On the other hand, Apriori-T with indexing enumeration tree is used for low cost FPM. A semiconductor manufacturing case study with Work In Progress data and true alarm data is used to proof the proposed algorithm. …”
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Thesis -
3
Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization
Published 2023“…Future research can explore more advanced machine learning algorithms, incorporate time-series analysis for temporal dependencies, and expand data collection from diverse organizational settings to improve the generalizability of predictive models.…”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks
Published 2015“…Simulation results show that the proposed algorithm converges and outperforms a source based tree algorithm. …”
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6
E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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7
Nano-scale VLSI clock routing module based on useful-skew tree algorithm
Published 2006“…We implemented Useful-Skew Tree (UST) algorithm which is based on the deferred-merge embedding (DME) paradigm, as the clock layout synthesis engine. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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10
Improved tree routing protocol in zigbee networks
Published 2010“…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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11
Delineating mangrove forest zone using spectral reflectance
Published 2020“…By using geospatial techniques and remotely sensed imagery data, the distribution of mangrove tree species associating with anthropogenic matrix can clearly be identified and mapped. …”
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12
White root disease auto-detection system for rubber trees based on dynamic electro-biochemical latex properties / Mohd Suhaimi Sulaiman
Published 2019“…All of the measurement inputs from the experiment were tested for the data distribution and discrimination between the conditions of the latex using statistical analysis. …”
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13
Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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15
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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17
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…However, by changing the distribution of both classes, the original classes distribution that are followed by that particular data will be violated. …”
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…This experiment show that the main factors that influence the spread of DHF in Bandung area are temperature, altitude, distribution of gender, and distribution of education levels. …”
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