Search Results - (( java implementation path algorithm ) OR ( based learning protocol algorithm ))

Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

“…The ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”

Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol by Sjaugi, Muhammad Farhan

“…The proposed algorithms based on node location information that may be collected through Global Positioning System (GPS). …”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Routing protocols strategies for flying Ad-Hoc network (FANET): Review, taxonomy, and open research issues by Almansor M.J., Din N.M., Baharuddin M.Z., Ma M., Alsayednoor H.M., Al-Shareeda M.A., Al-asadi A.J.

A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…The proposed ML-IDS achieved outstanding performance, with 24% reduction from the original size of the CICIDS-2018 dataset. Next, the ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”

Machine Learning For HTTP Botnet Detection Using Classifier Algorithms by Mohd Dollah, Rudy Fadhlee, Abd Majid, Mohd Faizal, Arif, Fahmi, Mas'ud, Mohd Zaki, Lee, Kher Xin

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A new particle swarm optimization for wireless mesh routing protocol by Abd. Rahman, Tharek

“…We test the propose algorithm in network simulator 2 (ns2). Based on the results, we proven that PSO-SIIW algorithm can be applied to MPR calculation in OLSR.…”
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A network aware based recommender system for VOIP application service in eLearning environment / Nazdiana Ab. Wahab by Ab. Wahab, Nazdiana

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Smart Microgrid QoS and Network Reliability Performance Improvement using Reinforcement Learning by Singh, N., Elamvazuthi, I., Nallagownden, P., Badruddin, N., Ousta, F., Jangra, A.

“…This paper proposes a reinforcement learning based methodology, Q-reinforcement Learning based Multi-agent based Bellmanford Routing (QRL-MABR), using multiple agents communicating over the microgrid network. …”
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A stable energy balancing based clustering routing protocol for IoUT using meta-heuristic technique by Ali, Elmustafa Sayed, Saeed, Rashid A, Eltahir, Ibrahim Khider, Khalifa, Othman Omran

“…In such networks, clustering approach enable to reduce the energy consumption in notable rate. In clustering based routing protocols, the cluster head (CH) must be carefully chosen. …”
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Mobility, Residual Energy, and Link Quality Aware Multipath Routing in MANETs with Q-learning Algorithm by Tilwari, Valmik, Dimyati, Kaharudin, Hindia, Mhd Nour, Fattouh, Anas, Amiri, Iraj

“…The MRLAM scheme uses a Q-Learning algorithm for the selection of optimal intermediate nodes based on the available status of energy level, mobility, and link quality parameters, and then provides positive and negative reward values accordingly. …”
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Applications of Machine Learning in Networking: A Survey of Current Issues and Future Challenges by Ridwan M.A., Radzi N.A.M., Abdullah F., Jalil Y.E.

A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

“…To address this challenge, the paper proposed XGB5hmC, a machine learning algorithm based on a robust gradient boosting algorithm (XGBoost), with different residue based formulation methods to identify 5hmC samples. …”

Intrusion detection on the in-vehicle network using machine learning by Sharmin, Shaila, Mansor, Hafizah

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The integration of Voip and e-Learning system in a collaborative learning environment / Ahmad Zulkhair Zakaria by Zakaria, Ahmad Zulkhair

“…Instead of developing the integration module, this project also run an analysis on the effect of VoIP based on UDP protocol and also proposed an algorithm to search an online NBPL’s Skype user.…”
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A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

“…The difficulty and impracticality of decrypting TLS network traffic before it reaches the Intrusion Detection System (IDS) has driven numerous research studies to focus on anomaly-based malware detection without decryption employing various features and Machine Learning (ML) algorithms. …”
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