Search results for " optimization."
showing 10 items of 2333 documents
Lévy Flights for Ant Colony Optimization in Continuous Domains
2009
In this paper, the authors propose the use of the Levy probability distribution as leading mechanism for solutions differentiation in an efficient and bio-inspired optimization algorithm, ant colony optimization in continuous domains, ACOR. In the classical ACOR, new solutions are constructed starting from one solution, selected from an archive, where Gaussian distribution is used for parameter diversification. In the proposed approach, the Levy probability distributions are properly introduced in the solution construction step, in order to couple the ACOR algorithm with the exploration properties of the Levy distribution.
Composite laminates buckling optimization through Levy based Ant Colony Optimization
2010
In this paper, the authors propose the use of the Levy probability distribution as leading mechanism for solutions differentiation in an efficient and bio-inspired optimization algorithm, ant colony optimization in continuous domains, ACOR. In the classical ACOR, new solutions are constructed starting from one solution, selected from an archive, where Gaussian distribution is used for parameter diversification. In the proposed approach, the Levy probability distributions are properly introduced in the solution construction step, in order to couple the ACOR algorithm with the exploration properties of the Levy distribution. The proposed approach has been tested on mathematical test functions…
A Reinforcement Learning Approach for User Preference-aware Energy Sharing Systems
2021
Energy Sharing Systems (ESS) are envisioned to be the future of power systems. In these systems, consumers equipped with renewable energy generation capabilities are able to participate in an energy market to sell their energy. This paper proposes an ESS that, differently from previous works, takes into account the consumers’ preference, engagement, and bounded rationality. The problem of maximizing the energy exchange while considering such user modeling is formulated and shown to be NP-Hard. To learn the user behavior, two heuristics are proposed: 1) a Reinforcement Learning-based algorithm, which provides a bounded regret and 2) a more computationally efficient heuristic, named BPT- ${K}…
Efficient tree construction for the multicast problem
2002
A new heuristic for the Steiner minimal tree problem is presented. The method described is based on the detection of particular sets of nodes in networks, the "hot spot" sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used as comparison terms in the experimental analysis which demonstrates the capability of the heuristic discussed.
Real-time content-aware image resizing using reduced linear model
2010
In this paper an effective and efficient method for contentaware image resizing is proposed. It is based on the solution of a linear system where each pixel displacement (compression or expansion) is determined in dependence of the visual relevance of the pixel itself. The linear nature of the model allows real-time application of the method even for large images. This fully automatic approach can be also improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results have proven that the presented method achieves results comparable or superior to existent strategies, while improving efficiency.
QoS-Aware Fault Detection in Wireless Sensor Networks
2013
Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical issues is the detection of corrupted readings amidst the huge amount of gathered sensory data. Indeed, such readings could significantly affect the quality of service (QoS) of the WSN, and thus it is highly desirable to automatically discard them. This issue is usually addressed through “fault detection” algorithms that classify readings by exploiting temporal and spatial correlations. Generally, these algorithms do not take into account QoS re…
Resilient hexapod robot
2017
In this paper, we present a method of learning desired behaviour of the specific robotic system and transfer of the existing knowledge in the event of partial system failure. Six-legged robot (hexapod) built on top of the Bioloid platform is used for the method verification. We use genetic algorithms to optimize the hexapod's gait, after which we simulate physical damage caused to the robot. The goal of this method is to optimize the gait in accordance with the actual robot morphology, instead of the assumed one. Also, knowledge that was previously gained will be transferred in order to improve the results. Nonstandard genetic algorithm with the specific mixed population is used for this.
Effective and Efficient Interpolation for Mutual Information based Multimodality Elastic Image Registration
2009
Mutual information (MI) is a popular similarity metric for multimodality image registration purpose. However, it is negatively influenced by artifacts due to interpolation effects. As a result, registration algorithms performance could be affected. In this paper a novel interpolation scheme is presented. It is both effective and efficient. Effective because it limits the presence of local maxima in the mutual information curve, efficient because it is simple to compute being based on simple and optimized distance measures. The method is validated and compared against other techniques both from performance and time complexity persepectives. Differently from other reference works, which perfo…
Real-Time Body Gestures Recognition Using Training Set Constrained Reduction
2017
Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition ac…
The Robotic Construction Kit as a Tool for Cognitive Stimulation in Children and Adolescents: The RE4BES Protocol
2019
Through numerous experiences, the robotics has been demonstrated to have good potential in the field of strengthening social skills in children with Special Educational Needs and in particular with autism spectrum disorder. There are still not many experimental studies on the cognitive enhancement and social skills of children with special needs conducted with robotics construction kits that, requiring both the construction of the robot body and the programming of its “mind“, bring into play a multiplicity of cognitive and social skills. For the aforementioned reasons our team from the University of Palermo and from the Center MetaIntelligenze ONLUS developed the treatment protocol RE4BES, …