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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
Published 2000“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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42
A parallel tabu search algorithm for VLSI standard-cell placement
Published 2000“…In this work, tabu search placement algorithm is parallelized on a network of workstations using PVM. …”
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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
Published 2023“…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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44
Computational evluation of protein energy functions
Published 2014“…In this project, we carry out a computational evaluation of putative protein energy functions. …”
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45
Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem
Published 1999“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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46
Random vector functional link network: Recent developments, applications, and future directions
Published 2023“…To overcome these issues, randomization based neural networks such as random vector functional link (RVFL) network have been proposed. RVFL model has several characteristics such as fast training speed, direct links, simple architecture, and universal approximation capability, that make it a viable randomized neural network. …”
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GAP - A GENETIC ALGORITHM APPROACH TO OPTIMIZE 2-BIT DECODER PLAS
Published 2020“…The number of product rows required for such PLas is a function of the assignment of pairs of variables to the decoders. …”
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48
A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
Published 2020“…This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. …”
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49
A new tabu search algorithm for the long-term hydro scheduling problem
Published 2002“…The proposed implementation contributes to the enhancement of speed and convergence of the original tabu search algorithm (TSA). A significant reduction in the objective function over previous classical optimization methods and a simulated annealing algorithm has been achieved. …”
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50
BUC algorithm for iceberg cubes
Published 2003“…In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. …”
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51
Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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From Collatz Conjecture to chaos and hash function
Published 2023“…By incorporating the Collatz process and carefully considering key-controlled variables, the proposed model aims to offer enhanced security properties while meeting the necessary criteria for a reliable and effective hashing mechanism. 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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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem
Published 2020“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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58
Thyristor controlled phase shifter based stabilizer design usingsimulated annealing algorithm
Published 1999“…This paper presents a thyristor controlled phase shifter (TCPS) based stabilizer design using the simulated annealing (SA) algorithm. …”
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59
Cross entropy error function in neural networks
Published 2002“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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60
Evolution Of Activation Functions for Neural Architecture Search
Published 2020“…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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