Search results for "computational intelligence"
showing 10 items of 50 documents
A Novel Expert System for Non-Invasive Liver Iron Overload Estimation in Thalassemic Patients
2014
Expert Systems can integrate logic based often on computational intelligence methods and they are used in complex problem solving. In this work an Expert System for classifying liver iron concentration in thalassemic patients is presented. In this work, an ANN is used to validate the output of the L.I.O.MO.T (Liver Iron Overload Monitoring in Thalassemia) method against the output of the state-of-the-art method based on MRI T2 assessment for liver iron concentration. The model has been validated with a dataset of 200 samples. The experimental Mean Squared Error results and Correlation show interesting performances. The proposed algorithm has been developed as a plug in for OsiriX Dicom View…
Advanced Topics in Intelligent Information and Database Systems
2017
This book presents recent research in intelligent information and database systems. The carefully selected contributions were initially accepted for presentation as posters at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) held from to 5 April 2017 in Kanazawa, Japan. While the contributions are of an advanced scientific level, several are accessible for non-expert readers. The book brings together 47 chapters divided into six main parts: • Part I. From Machine Learning to Data Mining.• Part II. Big Data and Collaborative Decision Support Systems,• Part III. Computer Vision Analysis, Detection, Tracking and Recognition,• Part IV. Data-Intensive Text P…
Computational Intelligence and Citizen Communication in the Smart City
2016
Information and communication are at the core of the intelligent city of tomorrow, and the key components of a smart city cannot prescind from data exchanges and interconnectedness. Citizen communication is an integral part of the smart city’s development plans: freedom of information and involvement in collective decisions, e-democracy and decision-making feedback can be greatly enhanced in an intelligent city, and, among other smart city components, foster a new era of participation and wise decisions. In this contribution we describe the methodologies that can be implemented in order to correctly develop automatic recognition systems for citizen communication, paying special attention to…
Exploiting the Human Factor in a WSN-Based System for Ambient Intelligence
2009
Practical applications of ambient intelligence cannot leave aside requirements about ubiquity, scalability, and transparency to the user. An enabling technology to comply with this goal is represented by wireless sensor networks (WSNs); however, although capable of limited in-network processing, they lack the computational power to act as a comprehensive intelligent system. By taking inspiration from the sensory processing model of complex biological organisms, we propose here a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part. WSNs act as a transparent interface that allows the system to understand human requirements through impl…
Design of complex sheet metal forming processes: a new computer aided progressive approach
2010
The growing interest in sheet metal stamping processes, particularly in automotive industry, led to three main issues in this field: request of very complex shapes; growing interest in springback control; solution of multi-objective problems. This makes the design of the sheet metal stamping processes very difficult, since the number of both design variables and design objectives are progressively increased; therefore, proper design methodologies to reduce times and costs are highly required. In this paper, an innovative design approach able to manage and optimize complex stamping operations is proposed. In particular, a progressive design approach based on the integration between numerical…
PORE Algorithm for Object Recognition in Photo Layers based on Parametric Characteristics of the Object Edges
2016
PORE stands for Photo-Object Recognition based on the Edges. Coincidentally, PORE means to examine something carefully and with due attention, so "we pore over the object layers in search for information about their characteristics with the aim at improving image recognition process". Therefore, this study presents a novel approach to object recognition based on the pattern by using photo layers and by defining the objects' specific characteristics. We select and introduce the parameters which determine a higher efficiency of image retrieval of the image objects. In this paper, we describe how the same photos are recognized in a process of classical retrieval compared to our model by analyz…
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
2017
Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approxim…
Hydrological post-processing based on approximate Bayesian computation (ABC)
2019
[EN] This study introduces a method to quantify the conditional predictive uncertainty in hydrological post-processing contexts when it is cumbersome to calculate the likelihood (intractable likelihood). Sometimes, it can be difficult to calculate the likelihood itself in hydrological modelling, specially working with complex models or with ungauged catchments. Therefore, we propose the ABC post-processor that exchanges the requirement of calculating the likelihood function by the use of some sufficient summary statistics and synthetic datasets. The aim is to show that the conditional predictive distribution is qualitatively similar produced by the exact predictive (MCMC post-processor) or …
Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems
2009
“Computational Intelligence” is an extremely wide-ranging and all-encompassing area. However, it is fair to say that the strength of a system that possesses “Computational Intelligence” can be quantified by its ability to solve problems that are intrinsically hard. One such class of NP-Hard problems concerns the so-called family of Knapsack Problems, and in this Chapter, we shall explain how a sub-field of Artificial Intelligence, namely that which involves “Learning Automata”, can be used to produce fast and accurate solutions to “difficult” and randomized versions of the Knapsack problem (KP).
Data Mining in Cancer Research [Application Notes
2010
This article is not intended as a comprehensive survey of data mining applications in cancer. Rather, it provides starting points for further, more targeted, literature searches, by embarking on a guided tour of computational intelligence applications in cancer medicine, structured in increasing order of the physical scales of biological processes.