Search Results - (( using function methods algorithm ) OR ( based integration model algorithm ))
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1
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The SEF has been extensively used to model the saturation nonlinearity. A major drawback of using the SEF function lies in its theoretical nature such that for a finite integration limit, the SEF become non-elementary integral and requires infinite series or numerical methods for evaluation. …”
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2
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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3
Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty
Published 2017“…To do this, Monte Carlo method with uniform function is used, then the stability of the proposed method towards demand uncertainty is shown. …”
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4
Neural network algorithm-based fall detection modelling
Published 2020“…The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
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5
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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6
Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement
Published 2020“…A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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7
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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8
Input Information in the Approximate Calculation of Two-Dimensional Integral from Highly Oscillating Functions (Irregular Case)
Published 2019“…The proposed formula is based on the algorithm, which is also effective for a class of discontinuous functions.…”
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Conference or Workshop Item -
9
Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…In this study, we propose a learning algorithm for the training of MLP models. Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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10
Development of an integrated scheduling model for handling equipment in automated port container terminals
Published 2014“…As the integrated scheduling of handling equipment is a “non-deterministic polynomialtime hard” (NP-hard) problem and also the computation time and ease of application are so important for real practices of the scheduling methods, So a meta-heuristic algorithm based on Genetic Algorithm is developed, in which, new operators create solutions considering the constraints of the problem and also a heuristic rule proposed which assigns the ALVs to the tasks. …”
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11
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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12
Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…Using the cross validation method the best training subset is selected to train the ANFIS model based on that dataset. …”
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13
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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14
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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15
An Approach to Derive Parametric L-System Using Genetic Algorithm
Published 2009“…This paper examines a method for automatic plant modeling which is based on an integration of GA and Parametric L-System using appropriate fitness function. …”
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Book Section -
16
Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm
Published 2021“…System identification was implemented via swarm intelligence algorithm known as cuckoo search algorithms based on auto regressive with exogenous model structure. …”
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Proceeding -
17
Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems
Published 2024“…This paper explores the tuning of the Sigmoid Proportional-Integral-Derivative (SPID) controller using variations of the Smoothed Functional Algorithm (SFA) for the underactuated Multiple-Input Multiple-Output (MIMO) twin-rotor system. …”
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18
Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner
Published 2022“…The iterative process of Broyden's approach is nearly identical to Newton's method. Meanwhile, the Levenberg-Marquadt method uses the gradient descent algorithm, which also has a similar algorithm to the Gauss-Newton method in finding the value for the unknown parameter.…”
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Student Project -
19
Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid
Published 2015“…In this project, the integral of time multiply squared error (ITSE) as the objective function is used on the ACE. …”
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20
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Integration of global search algorithm into ANN model further improved the model performance. …”
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