Search Results - (( java application interface algorithm ) OR ( parameter tuning learning algorithm ))
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Location accuracy improvement in bluetooth low energy based indoor positioning system for remote asset monitoring / Dasmond Roy Philips
Published 2024“…Combining both machine learning and parameters tuning approaches, lowest RMSE value of 0.015m was achieved. …”
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Thesis -
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR
Published 2005“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…This work proposes ITLBO as an FSS mechanism, and its algorithm-specific, parameterless concept (no parameter tuning is required during optimisation) was explored. …”
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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study
Published 2024“…However, its behavior strongly depends on some parameters, making tuning these parameters a sensitive step to maintain a good performance. …”
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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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A Chaotic Teaching Learning Based Optimization Algorithm for Optimization Emergency Flood Evacuation Routing
Published 2016“…Unlike competing work, the proposed work dwells on TLBO as parameter free algorithm (i.e. free from tuning). In this manner, the results reflect the actual algorithm’s optimal performance without the necessity of painstakingly difficult tuning process that potentially leads to false optimum solution. …”
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Conference or Workshop Item -
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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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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm
Published 2018“…Extreme learning machine (ELM) is utilized to tune the consequent parameters of the interval type 2 fuzzy logic system (IT2FLS). …”
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Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data
Published 2016“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The NTLBO was proposed in this paper as an FSS mechanism; its algorithm-specific, parameter-less concept (which requires no parameter tuning during an optimization) was explored. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
Published 2021“…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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Real-time algorithmic music composition application.
Published 2022“…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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Final Year Project / Dissertation / Thesis -
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LSSVM parameters tuning with enhanced artificial bee colony
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A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control
Published 2025“…In time-domain evaluations, the FGO-tuned softsign-FOPID exhibited the fastest rise time (0.0089 s), shortest settling time (0.0163 s), lowest overshoot (4.13%), and negligible steady-state error (0.0015%), surpassing the best-reported controllers in the literature, including the sine cosine algorithm-tuned PID, logarithmic spiral opposition-based learning augmented hunger games search algorithm-tuned FOPID, and manta ray foraging optimization-tuned real PIDD2. …”
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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…In order to ensure its search performance, HS requires extensive tuning of its four parameters control namely harmony memory size (HMS), harmony memory consideration rate (HMCR), pitch adjustment rate (PAR), and bandwidth (BW). …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Application-Programming Interface (API) for Song Recognition Systems
Published 2024“…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”
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A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems
Published 2017“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed algorithm benefits from the combination of extreme learning machine (ELM) and non-dominated sorting genetic algorithm (NSGAII) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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