Search Results - (( learning models learning algorithm ) OR ( java application optimisation algorithm ))
Search alternatives:
- application optimisation »
- optimisation algorithm »
- learning algorithm »
- java application »
- learning models »
- models learning »
-
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
Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…Then, the outcomes demonstrated that the best classifier for categorizing our data with 0.96% accuracy is the Decision Tree machine learning algorithm. When comparing the accuracy of a malware detection model, it is excellent if there are numerous machine learning algorithms and more malware datasets included.…”
Get full text
Get full text
Student Project -
3
A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market
Published 2023“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
Get full text
Get full text
Get full text
Article -
4
Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
Get full text
Get full text
Conference or Workshop Item -
5
Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
Get full text
Get full text
Conference or Workshop Item -
6
Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”
thesis::master thesis -
7
-
8
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
Get full text
Get full text
Get full text
Get full text
Proceedings -
9
-
10
Approach For Optimizing Course Recommendation Based On Integrating Modified Felder-Silverman Learning Style Model With Meta-Heuristics Algorithm
Published 2023“…It involves identifying potential courses learning style, validated through genetic and surrogate meta-heuristics optimization algorithms, and employing Felder-Silverman model for learning style identification. …”
Get full text
Get full text
Thesis -
11
Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches
Published 2024Subjects:Review -
12
Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…For the best practice machine learning pipelines, various machine learning models are used to discover the best model for CCRA study. …”
Get full text
Get full text
Thesis -
13
Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024Subjects:Conference Paper -
14
Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…However, deep learning algorithms, such as deep belief networks showed promising results in many domains, especially in image processing. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Article -
15
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
Get full text
Get full text
Get full text
Thesis -
16
An iterative incremental learning algorithm for complex-valued hopfield associative memory
Published 2016“…From the result of simulation experiment in terms of memory capacity and noise tolerance, the proposed model has the superior ability than the model with a complexvalued pseudo inverse learning algorithm.…”
Get full text
Get full text
Conference or Workshop Item -
17
Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
Get full text
Get full text
Article -
18
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. …”
Get full text
Get full text
Get full text
Thesis -
19
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
Get full text
Get full text
Thesis -
20
Wavelet network based online sequential extreme learning machine for dynamic system modeling
Published 2013“…Wavelet network (WN) has been introduced in many applications of dynamic systems modeling with different learning algorithms. In this paper an online sequential extreme learning machine (OSELM) algorithm adopted as training procedure for wavelet network based on serial-parallel nonlinear autoregressive exogenous (NARX) model. …”
Get full text
Conference or Workshop Item
