model-based optimization algorithms
Camera calibration optimization technique based on genetic algorithms
... method based on genetic optimization ...imaging model can be built through the ideal pinhole model radial distortion, tangential distortion and distortion correction affine and non-orthogonal; ...
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Search-Based Energy Optimization of Some Ubiquitous Algorithms
... search based techniques to optimize the energy efficiency of Quick- sort, Multi-Layer Perceptrons and popular suites of collection ...that optimization runs making use of O PACITOR can be distributed across ...
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Multi-objective analysis of machine learning algorithms using model-based optimization techniques
... Horn and Bischl (2016) survey whether these adaptions result in a reasonable SMBO variant. In their experiments, the performance measures false-positive rate and false-negative rate are op- timized simultaneously on nine ...
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Methods for efficient resource utilization in statistical machine learning algorithms
... learning algorithms based on the papers by Kotthaus et ...learning algorithms, we will focus solely on Model-Based Optimization (MBO), which is a learning algorithm with huge ...
153
Forecasting Short-term Electricity Demand in Residential Sector Based on Support Vector Regression and Fuzzy-rough Feature Selection with Particle Swarm Optimization
... precise model for one-month-ahead forecast of electricity demand in residential ...variables. Based on support vector regression and fuzzy-rough feature selection with particle swarm optimization ...
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Online Full Text
... decision-making model which, besides the application of NFs, uses optimization algorithms based on the rate of the return profit of each stock index to construct our NFs Model for a ...
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Optimal design of monopile offshore wind turbine structures using CBO, ECBO, and VPS algorithms
... design optimization of such structures is a fruitful yet, simultaneously, onerous task due to the tempestuous complexity of the problem, which mostly comes from their ...methodology based on meta-heuristic ...
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Fractured Reservoirs History Matching based on Proxy Model and Intelligent Optimization Algorithms
... global optimization [6]. They used the neural networks as a proxy model and showed that the required number of simulation runs to obtain a good history match can be reduced by the neural ...proxy ...
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Magnetic localization and orientation of the capsule endoscope based on a random complex algorithm
... paper, based on the magnetic dipole model as well as magnetic sensor array, we propose nonlinear optimization algorithms using a random complex algorithm, applied to the optimization ...
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MODELING AND SIMULATION OF GRID CONNECTED PHOTOVOLTAIC DISTRIBUTED GENERATION SYSTEM
... portfolio optimization algorithms, an improved ant colony optimization algorithm based on average entropy was ...portfolio optimization model, the improved algorithm is ...
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FACTS Controllers Tuning for Stability Improvement in Power System Using Soft Computing Technique
... PSO optimization algorithms to plan an SMIB based model for improvement of power system ...an optimization issue so as both GA and PSO optimization algorithms are able to ...
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The Discrete Particle Swarm Optimization Algorithms For Permutation Flowshop Scheduling Problem
... PSO-based algorithms to find the optimal sequence in ...combinatorial optimization problems in the ...mathematical model, proposed algorithm, case study, and parameter ...
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Meta Heuristics Algorithms: A Survey
... is based on the Producer- Scrounger model inspired by animal searching behavior and is ...good optimization algorithm ...algorithm based on the information of previous ...
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An overview of population-based algorithms for multi-objective optimisation
... rival algorithms (Hauschild and Pelikan 2011), it is not so trivial to generate the required probabilistic ...the model type strongly depends on the decision variable type, whether or not the decision ...
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Empirical Optimal Kernel for Convex Multiple Kernel Learning
... a model selection problem: the kernel weights are the hyperparameters of the classifier and are tuned based on the model selection criteria ...different algorithms: heuristic approach, ...
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Optimization of Closed-Loop Supply Chain Problem for Calculation Logistics Cost Accounting
... chain model (CLSCM) and propose a multi-objective genetic ...using optimization algorithms with the priority-based genetic algorithm (priGA), and Adaptive Weight Approach ...chain model ...
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Population-based optimization algorithms for solving the travelling salesman problem
... One of the other recent approaches for solving the TSP is proposed in (Song et al., 2006). In particular, the option that an ant hunts for the next step, the use of a combination of two kinds of pheromone evaluation ...
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High level dataflow network partitioning using stochastic algorithms
... partitioning algorithms used in this project are meant to be stochastic in ...the algorithms that are chosen are the PSO and ACO ...These algorithms were made to be used for different kinds of ...
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Bimodal scheduling for OBS networks and characterization of burst aggregation algorithms.
... aggregation algorithms [13], [21], [44], [47], [26] and [49] the arrival process of upper layer packets was assumed to follow a theoretical distribution, such as Poisson and ...aggregation algorithms using ...
145
Solving Quadratic Assignment Problem Using Water Cycle Optimization Algorithm
... water-cycle optimization algorithm performs better than Genetics, Cuckoo and Bee Colony algorithms, and in most comparisons, has better performance to other evolutionary algorithms in different test ...
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