Search Results - (( model evaluation step algorithm ) OR ( using optimization method algorithm ))
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1
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Finally, the initial partitioning is successively un-coarsened and re-refined back to the original hypergraph. These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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Thesis -
2
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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Article -
3
Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors
Published 2010“…First, the algorithms‘ performances were evaluated using numerical simulation employing two different scanning geometries: limited and full view scanning geometries, where the applicability of these algorithms was accessed by comparing the reconstructed images with actual model. …”
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4
System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
5
Using artificial intelligence search in solving the camera placement problem
Published 2022“…Following the coverage modeling, an optimization method needs to be used to locate the optimal poses and/or camera positions. …”
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6
Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…Second, is to develop the deep learning algorithm based on YOLOv3. Third step is to training and evaluate the model using loss function. …”
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Proceedings -
7
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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8
Evaluation of different control policies of semi-active MR fluid damper of a quarter-car model
Published 2012“…The performances of these models are evaluated to select a best model. The quarter-car model is executed using step input with two most common and effective control algorithm in vehicle suspension control which are linear quadratic regulator control, and Proportional Integral Derivative control algorithm. …”
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9
Enhancement of Single and Composite Images Based on Contourlet Transform Approach
Published 2009“…The objective evaluation steps show that the new method of enhancement not only superior to the commonly used transformation method (e.g. wavelet transform) but also to various spatial models (e.g. …”
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10
Breast cancer diagnosis through an optimization-driven multispectral gamma correction (ODMGC)
Published 2024“…The algorithm was successfully implemented in MATLAB 2020a, and the classifier was developed in Jupyter Notebook using Python. …”
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11
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…In addition, the mentioned block-matching algorithms are the baseline techniques that have been used to further develop all the enhanced or improved algorithms. …”
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Book Chapter -
12
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…The second segmentation algorithm combines Delaunay triangulation clustering in the spatial domain and Particle Swarm Optimization (PSO). …”
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13
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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14
Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir
Published 2020“…The porosity model obtained by conventional method in previous step would be used for primary evaluation of the rules. …”
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15
Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization
Published 2016“…We investigate the possible use of control theory, particularly theory on gradient ow system to derive some modified line search and trust region methods for optimization. …”
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16
Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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17
Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties
Published 2020“…Sensitivity analysis was then deployed using Standardized Regression Coefficients (SRC) method in order to analyse the correlation of the input uncertainties with the model output CSD. …”
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18
Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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19
Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. …”
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20
Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…Among the models used, the DLNN outperformed others, superiorly predicting landslide susceptibility. …”
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