Search Results - (( variable _ drop algorithm ) OR ( java application optimisation algorithm ))
Search alternatives:
- application optimisation »
- optimisation algorithm »
- java application »
- drop algorithm »
-
1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
Get full text
Get full text
Get full text
Article -
2
Neighbour-based on-demand routing algorithms for mobile ad hoc networks
Published 2017“…The dropping decision of the redundant RREQ in the NCPR algorithm completely relies on preset variables, such variables require to be set by the system administrator based on the scenario. …”
Get full text
Get full text
Get full text
Thesis -
3
-
4
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…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.…”
Get full text
Get full text
Thesis -
5
Simulation of single and dual layered rapid pressure swing adsorption
Published 2013“…The process variable profiles at CSS obtained from the algorithm are also found to be in excellent agreement with the MSS simulation. …”
Get full text
Get full text
Thesis -
6
Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…(iv) In addition, IWD has two variables that have a large effect on the performance and the convergence of the algorithm (Alijla et al., 2013). …”
thesis::doctoral thesis -
7
DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
Get full text
Get full text
Thesis -
8
Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman
Published 2025“…This approach tried to overcome the limitations of the manual method and traditional algorithm, which tends to fail with the diverse dataset, diverse visual features, and scalability. …”
Get full text
Get full text
Thesis -
9
Dynamic point stochastic rounding algorithm for limited precision arithmetic in Deep Belief Network training
Published 2017“…Using publicly available MNIST database, we show that the proposed algorithm can train a 3-layer DBN with an average accuracy of 98.49, with a drop of 0.08 from the double floating-point average accuracy. © 2017 IEEE.…”
Get full text
Get full text
Article -
10
Data dissemination in VANETs using clustering and probabilistic forwarding based on adaptive jumping multi-objective firefly optimization
Published 2022“…The metrics to be incorporated in the multi-objective optimizations are the packet delivery ratio (PDR), the end-to-end delay (E2E-delay) and the number of dropped packets. Comparing both AJ-MOFA and CFM with benchmarks using multi-objective optimization and networking metrics reveals the superiority in most evaluation measures, which makes them promising algorithms for data dissemination in VANETs. …”
Get full text
Get full text
Article -
11
Affine projection algorithm for speech enhancement using controlled projection order
Published 2020“…The method can be useful for clearer voice communication in variable environmental noise.…”
Get full text
Get full text
Get full text
Article -
12
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…Moreover, the LSA optimization technique is introduced to optimally determine the LSTM deep neural model hyperparameters including the number of hidden neurons, learn rate, epoch, learn rate drop factor, learn rate drop period, and gradient decay factor. …”
Article -
13
-
14
The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
Published 2010“…Moreover, the output from the ANNs will be utilized plus selected other input parameters as controlling variables for optimizing the production from a multiphase producing field using Genetic Algorithms (GA).…”
Get full text
Get full text
Get full text
Conference or Workshop Item -
15
Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study
Published 2010“…The data covered a wide range of variables such as oil rate (up to 25000 STB/D), water cut (up to 60%), angles of inclination (from -80 to 210), pipe length up to 26.0 km and pressure drop (from 10 to 250 psi). the model has been generated using the Back-propagation technique with Bayesian Regularization training algorithm for predicting pressure drop in pipelines under various angles of inclination. …”
Get full text
Get full text
Conference or Workshop Item -
16
Empowering Industry 5.0: Nurturing STEM tertiary education and careers through additional mathematics
Published 2024“…The proposed modified stacked AI predictive algorithm shows superior accuracy to benchmark algorithms. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Book Chapter -
17
Calculating customer experience management index for telecommunication service using genetic algorithm based weighted attributes
Published 2018“…The result of this research proved that there is positive and significant relationship between dependent variables.…”
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
18
A high-performance control scheme for photovoltaic pumping system under sudden irradiance and load changes
Published 2018“…The PV generator-side boost converter performs the maximum power point tracking (MPPT), while the IM−side two-level inverter regulates the net DC-link voltage and the developed electromagnetic torque by IM, which is coupled with a centrifugal pump. An improved variable step size perturb and observe (P&O) algorithm is proposed to reduce the steady-state PV power fluctuation, to accelerate the tracking operation under sudden irradiance changes, and to protect IM under load drops. …”
Get full text
Get full text
Article -
19
Analyzing students records to identify patterns of students' performance
Published 2023“…Finally, the results from the application of the CHAID algorithm aimed at predicting students' academic success is presented. � 2013 IEEE.…”
Conference Paper -
20
Artificial neural network for anomalies detection in distillation column
Published 2017“…The effect of these faults on process variables i.e. changes in distillate and bottom composition, distillate and bottom temperature, bottom flow rate, and the pressure drop is observed. …”
Get full text
Get full text
Article
