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method algorithm » mould algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications
Published 2019“…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. …”
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A decoding algorithm for I-Q space-time coded systems in fadingenvironments
Published 2000“…This paper presents the decoding of the I-Q space-time (ST) codes. The decoding problem of I-Q ST codes is formulated. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures
Published 2025“…This paper explores the calculation of European option prices on energy futures using a time-varying volatility model enhanced by a regime switching factor. …”
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Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
Published 2020“…In this paper, for the first time, a real-time implementation of SHM using an off-the-shelf mid-range microcontroller is presented and tested. …”
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Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives
Published 2005“…The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. The parameters for the GFLC are tuned by genetic algorithm (GA). …”
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A method for the minimum coloring problem using genetic algorithms
Published 2006“…This paper presents a method to solve the graph coloring problem for arbitrary graphs using genetic algorithms. The graph coloring problem, an NP-hard problem, has important applications in many areas including time tabling and scheduling, frequency assignment, and reg ister allocation. …”
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A method for test scheduling using an evolutionary approach. (c2000)
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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Real-Time Path-Planning using Depth/INS Sensor Fusion for Localization
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Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
Published 2022“…This paper presents a deep learning approach to forecast the cumulative number of COVID-19 cases using bidirectional Long Short-Term Memory (Bi-LSTM) network applied to multivariate time series. …”
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Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents
Published 2019“…It was observed that the linear classification algorithm was not able to detect heart attack in noisy data, whereas the support vector machine (SVM) algorithm with polynomial kernel with extended time–frequency features using extended modified B-distribution (EMBD) showed highest accuracy and was able to detect 97.4% and 96.3% of ST-elevation myocardial infarction (STEMI) and non-ST-elevation MI (NSTEMI), respectively. …”
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Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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A hybrid distributed test generation method using deterministic and genetic algorithms
Published 2017“…The algorithm is parallelized based on a cluster of workstations using the message passing interface (MPI) library. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
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