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processing algorithm » processing algorithms (Expand Search)
sample processing » image processing (Expand Search), melt processing (Expand Search)
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…In view of this, an innovative signal processing technique called a self-adaptive-smart algorithm (SASA) was designed and developed. …”
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42
Tensile Test Optimization Using the Design of Experiment and Soft Computing
Published 2023“…The objective of this study is to investigate the effects of temperature, the area of the contact point, and the operator on the tensile test of brass samples. This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”
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43
Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
doctoralThesis -
44
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
45
The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…During this process, the input patterns are categorized into different clusters. …”
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47
Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems
Published 2015Get full text
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49
Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks
Published 2023“…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …”
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50
Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
51
An optimal stochastic multivariable PID controller
Published 2019“…The development of the proposed algorithm aims for per-time-sample minimisation of the mean-square output error in the presence of erroneous initial conditions, measurement noise, and process noise. …”
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Complexity Avoidance using Biological Resemblance of Modular Multivariable Structure
Published 2014“…GFT (Genetic Fuzzimetric Technique) is of no exception which merges Fuzzy logic with genetic algorithm to achieve the optimization of the decision making process under uncertainty. …”
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54
Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 2024“…The proposed TCN-GWO uses both synchronously sampled values and synthetic values from various bus systems. …”
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55
A survey and comparison of wormhole routing techniques in a meshnetworks
Published 1997“…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …”
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Real-Time Implementation of GPS Aided Low Cost Strapdown Inertial Navigation System
Published 2009Get full text
doctoralThesis -
57
“Adaptive Control Technique Using Multilayer Feedforward Neural Networks”
Published 2005“…The proposed adaptive controller is a combination of a parameter estimation algorithm to estimate the parameters of the process and an adaptation algorithm for the connection weights of the neural network. …”
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58
Metallic coating thickness assessment over nonmagnetic metals using eddy current technology
Published 2019Get full text
doctoralThesis -
59
The Assessment and Allocation of Public Private Partnership Risks in the UAE
Published 2022Get full text
doctoralThesis -
60
Shuffled Linear Regression with Erroneous Observations
Published 2019“…The proposed algorithm aims for per-iteration minimization of the mean square estimate error. …”
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