Search Results - (( simulation organization learning algorithm ) OR ( java application path algorithm ))
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Octane number prediction for gasoline blends using convolution neural network / Zhu Yue
Published 2021“…At present, there are many prediction algorithms based on machine learning. According to the "80/20 rule" for building machine learning model, 80% of the time is spent of finding, cleaning, and organizing data, while the remaining 20% for training of the machine learning model. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review
Published 2023“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. …”
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Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah
Published 2015“…MATLAB and Vienna LTE simulators were used to conduct the experiments for the proposed algorithms, approaches and schemes and also used to verify the results. …”
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8
An ontology-based reasoning framework for reaction mechanisms simulation
Published 2007“…This work discusses a novel framework using Qualitative Reasoning (QR) to provide means for learning reaction mechanisms through simulation. The framework consists of a number of functional components. …”
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An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack
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Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies
Published 2022“…Effective removal and optimization models of metolachlor (MET) adsorption was carried out using MIL-53(Al) metalâ��organic framework (MOF), response surface methodology (RSM), artificial neural network (ANN) and molecular docking simulation. …”
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Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies
Published 2022“…Effective removal and optimization models of metolachlor (MET) adsorption was carried out using MIL-53(Al) metalâ��organic framework (MOF), response surface methodology (RSM), artificial neural network (ANN) and molecular docking simulation. …”
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Self-Organizing Network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah
Published 2016“…MATLAB and Vienna LTE simulators were used to conduct the experiments for the proposed algorithms, approaches and schemes and also used to verify the results……”
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Book Section -
15
On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay
Published 2024“…A comparative study based on machine learning algorithms was also conducted by using all features and the RFE-selected features to classify the R. rattus sample based on the age groups. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework
Published 2022“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework
Published 2022“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework
Published 2022“…The artificial neural network learning algorithm was employed to predict the adsorption of MET with high level of accuracy R2 0.999 and RMSE 0.047. …”
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