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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
carlo algorithm » search algorithm (Expand Search), colony algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
carlo algorithm » search algorithm (Expand Search), colony algorithm (Expand Search)
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161
Condenser capacity and hyperbolic perimeterImage 1
Published 2021“…We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …”
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162
Predicting stability of classes in an object-oriented system
Published 2010“…Nonetheless, it can be predicted based on other measurable software attributes such as cohesion, coupling, and complexity. …”
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163
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164
Structural similarity evaluation between XML documents and DTDs
Published 2007“…It is of polynomial complexity, in comparison with existing exponential algorithms. …”
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conferenceObject -
165
A simplified sliding‐mode control method for multi‐level transformerless DVR
Published 2022“…First, the use of FCS eliminates the modulator requirement, which reduces the design complexity in the practical implementation. Second, an effective method based on charging/discharging conditions of DC capacitors is proposed for balancing capacitor voltages using relevant switching state rather than combining DC voltage error with the inductor current error through a suitable weighting factor in forming the cost function. …”
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166
Digital Image Watermarking Using Balanced Multiwavelets
Published 2006“…In this paper, a robust watermarking algorithm using balanced multiwavelet transform is proposed. …”
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167
On the Generation of Quantified Lemmas
Published 2018“…This solution yields a sequence of lemmas and, finally, a proof based on these lemmas. Various techniques are developed to simplify the canonical solution resulting in a reduction of proof complexity. …”
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168
A method for efficient mapping and reliable routing for NoC architectures with minimum bandwidth and area
Published 2017“…Network-on-Chip (NoC) is an on-chip communication methodology that has been proposed as an alternative to bus-based communication in order to cope with the increased complexity in embedded designs. …”
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169
Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems
Published 2023“…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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170
Reinforcement R-learning model for time scheduling of on-demand fog placement
Published 2020“…Therefore, there is a need for an intelligent model capable of scheduling fog placement based on the user’s requests. In this paper, we propose a Fog Scheduling Decision model based on reinforcement R-learning, which focuses on studying the behavior of service requesters and produces a suitable fog placement schedule based on the concept of average reward. …”
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171
Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems
Published 2023“…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AASP&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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172
FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT
Published 2006“…SE is hybridized with force directed algorithm to speed-up the search. The proposed schemes are compared with previously presented SE based heuristics. …”
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173
An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks
Published 2022“…An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”
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174
Nonlinear Friction Identification of A Linear Voice Coil DC Motor
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175
Blood Glucose Regulation Modelling and Intelligent Control
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doctoralThesis -
176
Condenser capacity and hyperbolic perimeter
Published 2022“…<p dir="ltr">We study the conformal capacity by using novel computational algorithms based on implementations of the fast multipole method, and analytic techniques. …”
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177
Machine Learning Techniques for Pharmaceutical Bioinformatics
Published 2018“…The study integrates knowledge visualization, analysis, as well as development of a predictive model based on the Drug-Drug Interactions (DDIs) as a complex network. …”
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178
A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions
Published 2024“…The studied hybrid optimization MPPT methods are equated in terms of oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized. …”
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179
From Collatz Conjecture to chaos and hash function
Published 2023“…Most Chaos-based hash functions are insecure or inefficient due to their dependence on complex, attacked multi-dimensional maps or uncertain, weak one-dimensional maps like logistic and tent. …”
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180
Single-channel speech denoising by masking the colored spectrograms
Published 2025“…Similarly, it offers an improvement of 1 % in STOI and a reduction of 33 and 200 times, respectively, in network size and training epochs when compared to a complex variational U-Net-based model. Also, with comparable PESQ, the proposed system offers almost 2 % improvement in STOI, and a 2 times reduction in network size and 100 times reduction in training epochs, when compared to a lightweight system using automatic dimension reduction of network layers by a structured pruning method.…”