Search Results - (( development programme optimization algorithm ) OR ( java feature classification algorithm ))
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…It consists of 3-stage procedures: feature ranking, feature selection and classification. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The study proposes the use of software metric thresholds in the classification process during the GA representation. …”
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5
Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The data collected for this machine learning model is using the statistically significant features from vibration and acoustic analysis. The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024Conference Paper -
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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica...
Published 2021“…Originality/value: Attempted to develop a system with different optimization techniques. …”
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Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm
Published 2023“…There are many methods that can be used for power losses minimization such as Firefly Algorithm (FA), Ant Colony Optimization (ACO) and B-losses coefficient. …”
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Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod
“…This method provides magnificent speed up over than traditional sequential implementation methods while it sensitivity detection is still remained. To optimize the performance of the algorithm by exploiting parallelism in the design several techniques have been developed. …”
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Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using ASIC design flow / Nurzaima Mahmod
Published 2010“…This method provides magnificent speed up over than traditional sequential implementation methods while it sensitivity detection is still remained. To optimize the performance of the algorithm by exploiting parallelism in the design several techniques have been developed. …”
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12
Design of DNA sequence alignment accelerated system using 2-dimensional array and custom instruction on FPGA / Nur Dalilah Ahmad Sabri
Published 2018“…The proposed 2D Array on SW algorithm has been developed and designed by using ideas over previous work of CI on SW algorithm. …”
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13
Controller placement problem in the optimization of 5G based SDN and NFV architecture
Published 2021“…A heuristic called dynamic mapping and multi-stage CPP algorithm (DMMCPP) was developed to solve CPP as resource allocation in a distributed 5G-SDN-NFV-based network. …”
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14
Design and development of high performance swa cell design for local DNA sequence alignment
Published 2017“…This study proposed three new DNA sequence alignment accelerator system cell design and architecture based on the Smith-Waterman Algorithm (SWA) named as the new Optimized SWA Linear Gap Penalty (OSL), Optimized SWA Affine Gap Penalty (OSA), and Optimized Recursive Variable Expansion SWA Linear Gap Penalty (ORSL). …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima
Published 2020“…Particle swarm optimization (PSO), evolutionary particle swarm optimization (EPSO), and ant colony optimization (ACO) algorithms were applied to optimize the simultaneous LM strategies of peak clipping, valley filling and load shifting in order to minimize the energy consumption and maximum demand costs, and improve economic indexes such as load factor and building economic efficiency response. …”
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Lightweight PRINCE algorithm IP core for securing GSM messaging using FPGA
Published 2023“…An energy and cost-efficient implementation of PRINCE algorithm implemented in an environment of a microprocessor system using XILINX FPGA board is developed. …”
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Design and Implementation of Advanced Encryption Standard Using Verilog HDL
Published 2020“…The focus of this paper is to match with the existing cryptography algorithm, 128-bit Advanced Encryption Algorithm and improving the processing speed for the design with hardware implementation. …”
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Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin
Published 2018“…The MPPT method applied to track maximum power from PV panel is particle swarm optimization (PSO). Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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Development of a steady state visual evoked potential (SSVEP)-based brain computer interface (BCI) system
Published 2007“…The system includes a programmable visual stimulator, EEG amplifier with filter system, data acquisition card, and signal processing and classification algorithms. …”
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