Search results for "computational intelligence"
showing 10 items of 50 documents
Fuzzy environmental analogy index to develop environmental similarity maps for designing air quality monitoring networks on a large-scale
2019
All activities aimed at studying the primary causes and effects of air pollution cannot disregard the fact that it is necessary to have an optimal air quality monitoring network for assessing population exposure to air pollution and predicting the magnitude of the health risks. In the framework of a cooperation between the ARPA Sicilia Organization and the Department of Engineering, University of Palermo, research was performed to develop an innovative methodology useful for defining environmental similarity maps aimed at supporting the design of air quality monitoring networks at the regional scale. This approach is based on a new index called the fuzzy environmental analogy index (FEAI) b…
Best Proximity Point Results in Non-Archimedean Fuzzy Metric Spaces
2013
We consider the problem of finding a best proximity point which achieves the minimum distance between two nonempty sets in a non-Archimedean fuzzy metric space. First we prove the existence and uniqueness of the best proximity point by using di fferent contractive conditions, then we present some examples to support our best proximity point theorems.
Bot or not? a case study on bot recognition from web session logs
2018
This work reports on a study of web usage logs to verify whether it is possible to achieve good recognition rates in the task of distinguishing between human users and automated bots using computational intelligence techniques. Two problem statements are given, offline (for completed sessions) and on-line (for sequences of individual HTTP requests). The former is solved with several standard computational intelligence tools. For the second, a learning version of Wald’s sequential probability ratio test is used.
On automatic algorithm configuration of vehicle routing problem solvers
2019
Many of the algorithms for solving vehicle routing problems expose parameters that strongly influence the quality of obtained solutions and the performance of the algorithm. Finding good values for these parameters is a tedious task that requires experimentation and experience. Therefore, methods that automate the process of algorithm configuration have received growing attention. In this paper, we present a comprehensive study to critically evaluate and compare the capabilities and suitability of seven state-of-the-art methods in configuring vehicle routing metaheuristics. The configuration target is the solution quality of eight metaheuristics solving two vehicle routing problem variants.…
Ockham's Razor in Memetic Computing: Three Stage Optimal Memetic Exploration
2012
Memetic computing is a subject in computer science which considers complex structures as the combination of simple agents, memes, whose evolutionary interactions lead to intelligent structures capable of problem-solving. This paper focuses on memetic computing optimization algorithms and proposes a counter-tendency approach for algorithmic design. Research in the field tends to go in the direction of improving existing algorithms by combining different methods or through the formulation of more complicated structures. Contrary to this trend, we instead focus on simplicity, proposing a structurally simple algorithm with emphasis on processing only one solution at a time. The proposed algorit…
A Pareto optimal design approach for simultaneous control of thinning and springback in stamping processes
2009
One of the most relevant research issues in automotive field is focused on the reduction of stamped parts weight also increasing their strength. In this way, a strong research effort is developed on high strength steels which are widely utilized and they require a proper springback control. Springback reduction in sheet metal forming is a typical goal to be pursued which is conflicting with thinning reduction for instance. Thus, such problems can be considered as multi-objective ones characterized by conflicting objectives. What is more, nowadays, a great interest would be focused on the availability of a cluster of possible optimal solutions instead of a single one, particularly in an indu…
A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution
2011
Differential evolution has become one of the most widely used evolution- ary algorithms in multiobjective optimization. Its linear mutation operator is a sim- ple and powerful mechanism to generate trial vectors. However, the performance of the mutation operator can be improved by including a nonlinear part. In this pa- per, we propose a new hybrid mutation operator consisting of a polynomial based operator with nonlinear curve tracking capabilities and the differential evolution’s original mutation operator, to be efficiently able to handle various interdependencies between decision variables. The resulting hybrid operator is straightforward to implement and can be used within most evoluti…
Sviluppi della Intelligenza Computazionale: l'esempio del Sarcasm Detection
2016
Dopo un periodo prolungato in cui vigeva uno scarto persistente tra l’ottimismo dato dai grandi proclami di ricerca e la scarsità e frammentarietà di risultati veri e tangibili, viviamo (finalmente) nell’era delle grandi conquiste dell’Intelligenza Artificiale
Designing Cognitive Cities
2018
The following text intends to give an introduction into some of the basic ideas which determined the conception of this book. Thus, the first part of this article introduces the terms “City”, “Smart City” and “Cognitive City”. The second part gives an overview of design theories and approaches such as Action Design Research and Ontological Design (a concept in-the-making), in order to deduce from a theoretical point of view some of the principles that needs to be taken into account when designing the Cognitive City. The third part highlights some concrete techniques that can be usefully applied to the problem of citizen communication for Cognitive Cities (namely Metaheuristics, Fuzzy Sets a…
An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks
2007
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing the training of the neural network. This training is very challenging due to the large number of weights and noise caused by the dynamic neural network testing. The AGLMA is a memetic algorithm consisting of an evolutionary framework which adaptively employs two local searchers having different exploration logic and pivot rules. Furthermore, the AGLMA makes an adaptive noise compensation by means of explicit averaging on the fitness values and a dynamic population sizing which aims to follow the ne…