## Search

Now showing items 21-30 of 97

#### Journey to the center of the linear ordering problem

(2020-06)

A number of local search based algorithms have been designed to escape from the local optima, such as, iterated local search or variable neighborhood search. The neighborhood chosen for the local search as well as the ...

#### Probabilistic Load Forecasting Based on Adaptive Online Learning

(2020)

Load forecasting is crucial for multiple energy management
tasks such as scheduling generation capacity, planning
supply and demand, and minimizing energy trade costs. Such
relevance has increased even more in recent ...

#### Migration in Multi-Population Differential Evolution for Many Objective Optimization

(2020)

The paper proposes a novel extension of many objective optimization using differential evolution (MaODE). MaODE solves a many objective optimization (MaOO) problem by parallel optimization of individual objectives. MaODE ...

#### An efficient K-means clustering algorithm for tall data

(2020)

The analysis of continously larger datasets is a task of major importance in a wide variety of scientific fields. Therefore, the development of efficient and parallel algorithms to perform such an analysis is a a crucial ...

#### in-depth analysis of SVM kernel learning and its components

(2020)

The performance of support vector machines in non-linearly-separable classification problems strongly relies on the kernel function. Towards an automatic machine learning approach for this technique, many research outputs ...

#### Q-Learning Induced Artificial Bee Colony for Noisy Optimization

(2020)

The paper proposes a novel approach to adaptive selection of sample size for a trial solution of an evolutionary algorithm when noise of unknown distribution contaminates the objective surface. The sample size of a solution ...

#### Optimization of deep learning precipitation models using categorical binary metrics

(2020)

This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection or false alarm ...

#### Mutual information based feature subset selection in multivariate time series classification

(2020)

This paper deals with supervised classification of multivariate time se- ries. In particular, the goal is to propose a filter method to select a subset of time series. Consequently, we adopt the framework proposed by Brown ...

#### An adaptive neuroevolution-based hyperheuristic

(2020)

According to the No-Free-Lunch theorem, an algorithm that performs efficiently on any type of problem does not exist. In this
sense, algorithms that exploit problem-specific knowledge usually outperform more generic ...

#### Supervised non-parametric discretization based on Kernel density estimation

(2019-12-19)

Nowadays, machine learning algorithms can be found in many applications where the classifiers play a key role. In this context, discretizing continuous attributes is a common step previous to classification tasks, the main ...