Artificial Evolution
5th International Conference, Evolution Artificielle, EA 2001 Le Creusot, France, October 29–31, 2001 Selected Papers
Chapter and Conference Paper
Parkinson’s disease is a neurodegenerative disorder that often leads to abnormal atrophy in certain brain regions. Due to the ability to display brain structures non-invasively, magnetic resonance imaging (MRI...
Chapter and Conference Paper
Deep learning models have been widely studied and have achieved expert-level performance in medical imaging tasks such as diagnosis. Recent research also considers integrating data from various sources, for in...
Chapter
Automatically ranking comments by their relevance plays an important role in text mining. In this chapter, we introduce a new text digitization method: the bag-of-word clusters model, i.e., grou** semantic-r...
Chapter and Conference Paper
As computer vision has continued to make significant breakthroughs in recent years, medical image processing has become a research hotspot. However, hospitals that generate medical images have difficulty shari...
Chapter
Machine learning and model checking are two types of intelligent computing techniques that have been widely used to study different complicated systems nowadays. It is well-known that the cellular functions an...
Chapter and Conference Paper
Molecular communication (MC) is an emerging communication method using molecules or particles as signal carriers, which enables nanomachines to send messages at the nano- or micro-nano scale for information ex...
Chapter and Conference Paper
Biological networks describe the relationships among molecular elements and help in the deep understanding of the biological mechanisms and functions. One of the common problems is to identify the set of biomo...
Chapter and Conference Paper
Wireless sensor networks is an important component of Internet of everything, and can be deployed in many applications, such as search and rescue, border patrols, environmental monitoring, and combat scenarios...
Chapter and Conference Paper
In this paper, the Re (Reynolds number)-dependence of the unsteady aerodynamics in a flap**-flying insect was investigated. To this end, we developed a multi-block- and overset-grid-based in-house CFD solver an...
Chapter and Conference Paper
Gene selection aims at identifying a (small) subset of informative genes from the initial data in order to obtain high predictive accuracy. This paper introduces a new wrapper approach to this difficult task w...
Chapter and Conference Paper
We have proposed an ant-based clustering algorithm for document clustering based on the travelling salesperson scenario. In this paper, we presented an approach called Ant-MST for gene expression data clusteri...
Chapter and Conference Paper
Ovarian cancer is a primary gynecological cancer which pathological stages include benign, borderline and invasive stages cause death in many countries. In this paper, linear regression, analysis of variance (...
Chapter and Conference Paper
Protein-protein interactions play a very important role in many biological processes, for example, information transfer along signaling pathways, and enzyme catalysis. Recently, scientists tried to predict the...
Chapter and Conference Paper
We present PICPA, a new algorithm for tackling constrained continuous multi-objective problems. The algorithm combines constraint propagation techniques and evolutionary concepts. Unlike other evolutionary algori...
Book and Conference Proceedings
5th International Conference, Evolution Artificielle, EA 2001 Le Creusot, France, October 29–31, 2001 Selected Papers
Chapter and Conference Paper
In this paper, we present a first scatter search approach for the Graph Coloring Problem (GCP). The evolutionary strategy scatter search operates on a set of configurations by combining two or more elements. New ...
Chapter and Conference Paper
This paper presents an analysis of the search space of the well known NP-complete SAT problem. The analysis is based on a measure called “density of states” (d.o.s). We show experimentally that the distributio...