Search Results - (( customer satisfaction learning algorithm ) OR ( java simulation optimization algorithm ))
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1
Towards real-time customer satisfaction prediction model for mobile internet networks
Published 2018“…To this end, the implementation phase has employed machine learning algorithms in the Microsoft Machine Learning R client Server. …”
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Book Section -
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. …”
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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. …”
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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). …”
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Monograph -
5
Customer behavior analysis based on purchasing history and reviews using automated decision-making systems
Published 2025“…Machine Learning Techniques for Customer Behavior Analysis: Customer satisfaction can be identified for online purchasing using the machine learning method. …”
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6
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 -
7
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. …”
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Thesis -
8
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. …”
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9
Machine learning based route optimization for the travelling salesman problem with pickup and delivery
Published 2023“…Consequently, the courier cost will increase, which leads to in low customer satisfaction due to long pickup and delivery time, particularly during peak hours. …”
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Final Year Project / Dissertation / Thesis -
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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…This study aims to identify telecom customer segments by utilizing machine learning and subsequently develop a web-based dashboard. …”
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Article -
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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.…”
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Monograph -
12
Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. Effective CHFS is crucial for achieving production balance, reducing costs, and improving customer satisfaction. …”
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13
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. …”
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14
Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour
Published 2022“…The accuracy of the labor division is very important to get customer satisfaction. Inappropriate work distribution can increase complaints from customers. …”
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Proceeding Paper -
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Fundamentals of Entreoreneurship ENT 300 : Preloved By Qysqus / Nur Qystyna Nasharuddin
Published 2021“…In order to give an outstanding satisfaction to the customers, my company hand picked every item to make sure the quality is at its best and also up to date. …”
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Entrepreneurship Project -
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Article -
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Product Recommendation System (Targeted Recommendation using Deep Learning in Computer Vision)
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Undergraduates Project Papers -
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A review and comparative analysis of predictive models for supply chain demand forecasting
Published 2026“…This study reviews key techniques, including statistical time-series models, supervised and unsupervised learning algorithms, ensemble methods, and deep learning architectures. …”
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Proceeding Paper -
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A collaborative filtering approach using machine learning and business intelligence: a critical review
Published 2025“…Specifically, we discovered that combining deep learning techniques with reinforcement learning algorithms enhanced recommendation reliability by 35% while improving user engagement measures by 25%. …”
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Article -
20
SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing
Published 2019“…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. SecPath is evaluated with several variations using 400 nodes in WSN deployments as well as large-scale simulations. …”
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