Showing 1 - 20 results of 77 for search '(( algorithm state functional ) OR ((( algorithm python function ) OR ( algorithm co function ))))', query time: 0.13s Refine Results
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    Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

    Published 2018
    “…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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    Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks by Haris M. Khalid (17017743)

    Published 2023
    “…To address this issue, a median regression function (MRF)-based state estimation is presented in this paper. …”
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    Finite state machine state assignment for area and power minimization by El-Maleh, A.

    Published 2006
    “…In this paper, we address the problem of FSM state assignment to minimize area and power. The objectives are targeted as single/independent as well as multi-objective optimization (MOP) problems. …”
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    Computational evluation of protein energy functions by Mansour, Nashat

    Published 2014
    “…A protein is characterized by its 3D structure, which defines its biological function. Proteins fold into 3D structures in a way that leads to low-energy state. …”
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    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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    Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

    Published 1998
    “…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …”
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    Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

    Published 2003
    “…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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    A new multimodulus blind equalization algorithm by Abrar, Shafayat

    Published 2004
    “…The steady-state performance of the proposed algorithm is demonstrated by simulations. …”
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    Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

    Published 2022
    “…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …”
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    Belief selection in point-based planning algorithms for POMDPs by Azar, Danielle

    Published 2017
    “…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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    Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

    Published 2023
    “…This paper evaluates and compares the proposed model with state-of-the-art methods on sixteen time series. …”
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    Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

    Published 2022
    “…The results show that the performance of the SCA-βHC algorithm is increased by tuning its parameters in proper value. …”
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    Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

    Published 2025
    “…We develop a semi-analytical method to determine the price of European options on these energy futures, involving the derivation of the characteristic function for the energy futures' dynamics. To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …”
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