Search Results - (( based optimization based algorithm ) OR ( based interactive learning algorithm ))
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1
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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2
Software module clustering based on the fuzzy adaptive teaching learning based optimization algorithm
Published 2019“…Although showing competitive performances in many real-world optimization problems, Teaching Learning based Optimization Algorithm (TLBO) has been criticized for having poor control on exploration and exploitation. …”
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3
Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
Published 2019“…ATLBO is a recent enhanced variant of Teaching Learning-based Optimization (TLBO) algorithm that adaptively applies its search operations using a Mamdani-type fuzzy inference system. …”
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4
Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
Published 2022“…A step towards long network performance optimization is theterm use of deep reinforcement learning (DRL), which can learn the best policy via interaction with the environment. …”
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5
Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing
Published 2017“…In simple terms, a pairwise testing strategy significantly minimizes large input parameter values (or configuration options) of a system into a smaller set based on pairwise interaction (or combination). Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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Thesis -
7
How Does Image Complexity Affect the Accuracy of an Interactive Image Segmentation Algorithm?
Published 2025“…By introducing a dynamic stroke allocation approach and evaluating different configurations, the research provides insights into optimizing accuracy based on image complexity. The adaptive strategy improves segmentation performance and guides the development of robust algorithms. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…The results show the Q-EMCQ is also capable of outperforming the original EMCQ as well as several recent meta/hyper-heuristic including modified choice function, Tabu high-level hyperheuristic, teaching learning-based optimization, sine cosine algorithm, and symbiotic optimization search in clustering quality within comparable execution time.…”
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9
Operating a reservoir system based on the shark machine learning algorithm
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10
An adaptive HMM based approach for improving e-Learning methods
Published 2023“…The evolution of web based interaction and information processing has provided an important platform to conduct e-learning activities. …”
Conference Paper -
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…Our deep learning method also performs the atomic morphological operations and shadow removal based on the hue saturation value color space. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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13
Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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16
Temporal integration based factorization to improve prediction accuracy of collaborative filtering
Published 2016“…The TemporalMF++ approach relies on the k-means algorithm and the bacterial foraging optimization algorithm. …”
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Thesis -
17
Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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18
A Tabu Search Hyper-Heuristic for t-way Test Suite Generation
Published 2016“…HHH adopts Tabu Search as its high level meta-heuristic and leverages on the strength of four low level meta-heuristics, comprising of Teaching Learning Based Optimization, Global Neighborhood Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm. …”
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Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design
Published 2023“…We believe that with the reuse of past cases for solving new problems, new framework users will be able to dramatically improve their software development performance. The use of rule-based reasoning and genetic algorithms will optimize the case search and case adaptation process. �2008 IEEE.…”
Conference Paper -
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A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…The Fast Learning Network (FLN) is one of the new machine learning algorithms that are easy to implement, computationally efficient, and with excellent learning performance characteristics. …”
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