Search Results - (( learning models path algorithm ) OR ( java simulation optimization algorithm ))
Search alternatives:
- learning models »
- java simulation »
- path algorithm »
-
1
Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…Our model can generate an appropriate learning path for learners based on their background and job goals. …”
Get full text
Get full text
Article -
2
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
Get full text
Get full text
Article -
3
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
Get full text
Get full text
Get full text
Thesis -
4
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
Get full text
Get full text
Get full text
Monograph -
5
Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
thesis::doctoral thesis -
6
Solving the optimal path planning of a mobile robot using improved Q-learning
Published 2019“…Q-learning, a type of reinforcement learning, has gained increasing popularity in autonomous mobile robot path planning recently, due to its self-learning ability without requiring a priori model of the environment. …”
Get full text
Get full text
Get full text
Article -
7
Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…Firstly, the study concludes that the adoptions of the flexible approach in estimation can model the binary feature of CVDs and non-linear paths in the complex path models. …”
Get full text
Get full text
Thesis -
8
Path Following Using A Learning Neural Network
Published 2004“…The implemented neural controller will in turn minimize a performance index, which includes the lateral and attitude angle errors ofvehicle models with respect to the paths. The thesis differs from [2] in a sense that different types of neural controller are established to achieve a better path following accuracy. …”
Get full text
Get full text
Final Year Project -
9
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
10
Design of Modeling Elements of Luoshan Shadow Puppets Creative Goods Based on Deep Learning
Published 2023“…In this paper, based on the design of modeling elements of mountain shadow puppets, the characteristics of visual elements of shadow puppets creative goods are analyzed, and an intelligent design algorithm of shadow puppets creative goods based on deep learning (DL) is innovatively proposed. …”
Get full text
Get full text
Get full text
Proceeding -
11
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
Get full text
Get full text
Thesis -
12
Suicide and self-harm prediction based on social media data using machine learning algorithms
Published 2023“…In combined with robust machine learning algorithms, social networking data may provide a potential path ahead. …”
Get full text
Get full text
Get full text
Article -
13
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
Get full text
Get full text
Thesis -
14
Implementation of machine learning algorithm in preventing network congestion
Published 2023text::Final Year Project -
15
-
16
Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
Get full text
Get full text
Get full text
Get full text
Monograph -
17
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
Get full text
Get full text
Thesis -
18
-
19
-
20
Development of an Adaptive Algorithm for Solving the Inverse Kinematics Problem for Serial Robot Manipulators
Published 2005“…The proposed technique does not require any prior knowledge of the kinematics model of the system being controlled; the main idea of this approach is the use of an Artificial Neural Network to learn the robot system characteristics rather than having to specify an explicit robot system model.Since one of the most important problems in using Artificial Neural Networks, is the choice of the appropriate networks' configuration, two different networks' configurations were designed and tested, they were trained to learn desired set of joint angles positions from a given set of end effector positions. …”
Get full text
Get full text
Thesis
