Search results for "algorithm."

Oxidative stability of virgin olive oil: evaluation and prediction with an adaptive neuro-fuzzy inference system (ANFIS).

2019

Background An adaptive neuro-fuzzy inference system (ANFIS) was employed to predict the oxidative stability of virgin olive oil (VOO) during storage as a function of time, storage temperature, total polyphenol, α-tocopherol, fatty acid profile, ultraviolet (UV) extinction coefficient (K268 ), and diacylglycerols (DAGs). Results The mean total quantities of polyphenols and DAGs were 1.1 and 1.9 times lower in VOOs stored at 25 °C than in the initial samples, and the mean total quantities of polyphenols and DAGs were 1.3 and 2.26 times lower in VOOs stored at 37 °C than in the initial samples, respectively. In a single sample, α-tocopherol was reduced by between 0.52 and 0.91 times during sto…

Measuring trunk orientation with a CMOS camera: feasibility and accuracy.

2007

International audience; The purpose of this study was to develop and validate a new tool to objectively quantify trunk orientation at the bedside, especially dedicated to the measurement of the lateropulsion in acute and subacute stroke patients. We developed software to analyze 2D movement with a CMOS camera (Logitech Quickcam Pro 4000) and to calculate the orientation of a segment defined by two color markers. First, the accuracy, reproducibility and noise when measuring segment orientations were evaluated with the CMOS camera placed in different positions, and second trunk orientation was measured in static and in dynamic conditions both with a CMOS camera and with a gold standard 3D vid…

Evaluating a hierarchical approach to landscape-level harvest scheduling

2018

Forest planning at the landscape level has the potential to become a large intractable problem. In Finland, Metsähallitus (the state enterprise that manages federally owned land) creates strategic plans to determine the appropriate harvest level. While these plans are feasible, they are not implementable in practice as the harvests are scattered temporally and spatially. Requiring that harvests be organized both temporally and spatially for practical implementation can result in an intractable problem. Through a hierarchical approach, the problem can be organized into steps in which the intractable problem is broken down into smaller easily solvable parts. As an approximation technique, th…

Optimizing Query Perturbations to Enhance Shape Retrieval

2020

3D Shape retrieval algorithms use shape descriptors to identify shapes in a database that are the most similar to a given key shape, called the query. Many shape descriptors are known but none is perfect. Therefore, the common approach in building 3D Shape retrieval tools is to combine several descriptors with some fusion rule. This article proposes an orthogonal approach. The query is improved with a Genetic Algorithm. The latter makes evolve a population of perturbed copies of the query, called clones. The best clone is the closest to its closest shapes in the database, for a given shape descriptor. Experimental results show that improving the query also improves the precision and complet…

Reverse-safe data structures for text indexing

2021

We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…

An Interactive Framework for Offline Data-Driven Multiobjective Optimization

2020

We propose a framework for solving offline data-driven multiobjective optimization problems in an interactive manner. No new data becomes available when solving offline problems. We fit surrogate models to the data to enable optimization, which introduces uncertainty. The framework incorporates preference information from a decision maker in two aspects to direct the solution process. Firstly, the decision maker can guide the optimization by providing preferences for objectives. Secondly, the framework features a novel technique for the decision maker to also express preferences related to maximum acceptable uncertainty in the solutions as preferred ranges of uncertainty. In this way, the d…

A New Paradigm in Interactive Evolutionary Multiobjective Optimization

2020

Over the years, scalarization functions have been used to solve multiobjective optimization problems by converting them to one or more single objective optimization problem(s). This study proposes a novel idea of solving multiobjective optimization problems in an interactive manner by using multiple scalarization functions to map vectors in the objective space to a new, so-called preference incorporated space (PIS). In this way, the original problem is converted into a new multiobjective optimization problem with typically fewer objectives in the PIS. This mapping enables a modular incorporation of decision maker’s preferences to convert any evolutionary algorithm to an interactive one, whe…

2019

Worries about possible harmful effects of new technologies (modern health worries) have intensely been investigated in the last decade. However, the comparability of translated self-report measures across countries is often problematic. This study aimed to overcome this problem by developing psychometrically sound brief versions of the widely used 25-item Modern Health Worries Scale (MHWS) suitable for multi-country use. Based on data of overall 5,176 individuals from four European countries (England, Germany, Hungary, Sweden), Ant Colony Optimization was used to identify the indicators that optimize model fit and measurement invariance across countries. Two scales were developed. A short (…

Fuzzy Portfolio Selection Models for Dealing with Investor’s Preferences

2017

This chapter provides an overview of the authors’ previous work about dealing with investor’s preferences in the portfolio selection problem. We propose a fuzzy model for dealing with the vagueness of investor preferences on the expected return and the assumed risk, and then we consider several modifications to include additional constraints and goals.

Impact of decision horizon on post-prognostics maintenance and missions scheduling: a railways case study

2021

International audience; In this paper, we propose a study of the decision horizon duration for rolling stock mission assignment and maintenance planning in a prognostics and health management (PHM) context. The aim is to determine the best decision horizon duration that allows the con- struction of a suitable schedule that assigns railway vehicles to missions and integrates required maintenance operations accord- ing to the current and future health of the vehicles. A genetic algorithm is used to minimize the overall cost of the joint schedule as a function of the decision horizon. The results are compared to three proposed heuristics to study the influence of the resolution method on the d…