AI Medical Compendium Topic

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Problem Solving

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Fuzzy-Rough Cognitive Networks.

Neural networks : the official journal of the International Neural Network Society
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different cl...

The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem.

Computational intelligence and neuroscience
A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization...

A biologically inspired controller to solve the coverage problem in robotics.

Bioinspiration & biomimetics
The coverage problem consists on computing a path or trajectory for a robot to pass over all the points in some free area and has applications ranging from floor cleaning to demining. Coverage is solved as a planning problem-providing theoretical val...

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

PloS one
Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization proble...

Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning.

Evolutionary computation
This article tackles the Distribution Network Expansion Planning (DNEP) problem that has to be solved by distribution network operators to decide which, where, and/or when enhancements to electricity networks should be introduced to satisfy the futur...

A time-delay neural network for solving time-dependent shortest path problem.

Neural networks : the official journal of the International Neural Network Society
This paper concerns the time-dependent shortest path problem, which is difficult to come up with global optimal solution by means of classical shortest path approaches such as Dijkstra, and pulse-coupled neural network (PCNN). In this study, we propo...

An artificial intelligence framework for compensating transgressions and its application to diet management.

Journal of biomedical informatics
Today, there is considerable interest in personal healthcare. The pervasiveness of technology allows to precisely track human behavior; however, when dealing with the development of an intelligent assistant exploiting data acquired through such techn...

A new neural network model for solving random interval linear programming problems.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming prob...

An efficient automatic workload estimation method based on electrodermal activity using pattern classifier combinations.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Automatic workload estimation has received much attention because of its application in error prevention, diagnosis, and treatment of neural system impairment. The development of a simple but reliable method using minimum number of psychophysiologica...

A neurodynamic approach to convex optimization problems with general constraint.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neurodynamic approach with a recurrent neural network for solving convex optimization problems with general constraint. It is proved that for any initial point, the state of the proposed neural network reaches the constraint set...