Search Results - (( java application optimisation algorithm ) OR ( basic comparing tree algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Prior to localization of the base of young corn tree, skeletonizing operation is performed to get the basic shape of the object. …”
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Network analysis on safety culture and worker‘s behaviour : A forest of all minimum spanning trees by Djauhari, Maman A., Sharif, Shamshuritawati, Djauhari, Hariza

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Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

“…The basic principle of TM simplifies the plant growth into shoots and roots part. …”
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Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

“…The basic principle of TM simplifies the plant growth into shoots and roots part. …”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

“…The algorithm defined in this study was evaluated with manual measurements as reference, and the morphological parameters of the canopy obtained using the LOAM and LeGO-LOAM algorithms as the basic framework were compared. …”
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Comparison of path planning in simulated robot by Ch’ng, Chee Yu’ng

“…There are 4 path planning algorithms will be compared, which are Dijkstra’s algorithm, A* algorithm, RapidExploring Random Tree (RRT) algorithm, and the last one is an algorithm modified from A*. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Optimized scheme for efficient and scalable key management in IEEE 802.16e-based networks by Sadeghi, Mohammad Mehdi Gilanian

“…To generate, update and distribute the keys for secure communication over IEEE 802.16e, the MBS applies Multicast and Broadcast Rekeying Algorithm (MBRA) as a basic key management algorithm. …”
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Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta... by Keiko Ioki, Daniel James, Phua, Mui How, Satoshi Tsuyuki, Nobuo Imai

“…Here, we compared structural characteristics and tree community composition of old growth forest and secondary forests in a montane region of Sabah, Malaysia, which experienced five different anthropogenic disturbances. …”
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Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

“…Finally, the Buildings Footprint developed based on the algorithm was compared with the Buildings Footprint developed manually to assess the accuracy of the results. …”
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AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking by Wisitponchai, Tanchanok, Shoombuatong, Watshara, Lee, Vannajan Sanghiran, Kitidee, Kuntida, Tayapiwatana, Chatchai

“…Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with ≥1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”

Development of an Activity Recognition System Using Accelerometers by Hui, Dandy Lau Jing

“…With accelerometers that capture the acceleration rate of different activities and Decision Tree algorithm for classification, the system is able to predict accurately the activity performed by the wearer. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

“…More significantly, this paper empirically discusses and compares the performances of six supervised machine learning algorithms, known as K-Nearest Neighbors (K-NN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and Logistic Regression (LR), which are commonly used in the literature for detecting malware apps.…”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

“…Moreover, the performances of both BrC detection and BrT classification are compared with existing state-of-art baseline studies. …”
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Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach by Pinto, Mavin Jason, Sharath, S. S., Sudhakar, K., Priya, S. Shanmuga, Thirunavukkarasu, I.

“…The findings revealed that CatBoost is most suitable with R2 of 0.99 for training and 0.87 for test, and RMSE of 0.184 compared to the other 5 algorithms. AdaBoost, XGBoost, GBDT, LightGBM, and RF performed in an acceptable range. …”
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