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1
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…A modified fitness function in Wrapper GA was introduced by adding a function to maintain the balanced of the selected features. …”
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2
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…Hence, we proposed a complete method by combining MBPSO, MKN and GK (MBPSO+MKN+GK). The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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3
Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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Conference or Workshop Item -
4
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…In particular, the search capacity of the MVO algorithm has been improved using the sine and cosine functions of the Sine Cosine Algorithm (SCA) that will be able to balance the processes of exploration and exploitation. …”
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5
Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…The prototype of SEM is constructed based on the modern Smart Meter design and modified with additional control devices and sensors, so that it can measure, record and transfer the data using designated algorithm combining three types of communication system in one device; Wi-Fi, GSM and RF. …”
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6
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…In addition, an improvement is made in the third sub-algorithm where the minimum output residual is combined with the cost function. …”
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7
Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong
Published 2018“…The computational results also show that the algorithms of population based ACO performs better than the algorithms of non-population based ACO. …”
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8
An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting
Published 2023“…SVR-ABO uses the classical ABO approach. SVR-popABO enhances population diversity using a chaotic function. …”
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9
Modelling of multi-robot system for search and rescue
Published 2023“…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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Final Year Project / Dissertation / Thesis -
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Article -
11
Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution
Published 2006“…The mutual information algorithms used in this work has been developed and experimented in the system and has proven to yield more accurate and stable results than other algorithms. …”
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12
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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13
Solving optimal power flow problem with stochastic wind–solar–small hydro power using barnacles mating optimizer
Published 2021“…In this paper, recent metaheuristic algorithm namely Barnacles Mating Optimizer (BMO) will be used to solve three objective functions of OPF problem viz. (1) cost minimization of the power generation that consists of thermal and stochastic wind–solar–small hydro power generations, (2) power loss minimization, and (3) combined cost and emission minimization of mentioned power generations. …”
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Multiple and solid data background scheme for testing static single cell faults on SRAM memories
Published 2013“…This method is evaluated in terms of function and performance differences between the proposed MTA and existing MTA using the User Defined Algorithm (UDA) available in the MBISTArchitect tool. …”
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16
A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
Published 1999“…The methods employ a hybrid descent direction strategy which uses a linear convex combination of quasi-Newton BFGS and steepest descent as search direction. …”
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Testing of linear models for optimal control of second-order dynamical system based on model-reality differences
Published 2021“…Consequently, a modified model-based optimal control problem has resulted. …”
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Testing of linear models for optimal control of second-order dynamical system based on model-reality differences
Published 2021“…Consequently, a modified model-based optimal control problem has resulted. …”
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Testing of linear models for optimal control of second-order dynamical system based on model-reality differences
Published 2021“…Consequently, a modified model-based optimal control problem has resulted. …”
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Implementation and simplification of an Output Shifted Coding Modulation (OSCM) on a high speed DSP processor / Roslina Mohamad, Wan Nor Syafizan Wan Muhamad and Rosmalini Abdul Ka...
Published 2009“…The new coded modulation is called as Output Shifted Coding Modulation (OSCM). This algorithm also shows that by using low constraint length convolutional component codes, it can outperform the convolutional codes using Viterbi decoders with much higher constraint lengths. …”
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