Search results for "A* algorithm"
showing 10 items of 2538 documents
Tolerating malicious monitors in detecting misbehaving robots
2008
This paper considers a multi–agent system and focuses on the detection of motion misbehavior. Previous work by the authors proposed a solution, where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors. In this work, we consider possible failure of monitors that may send incorrect information to their neighbors due to spontaneous or even malicious malfunctioning. In this context, we propose a distributed software architecture that is able to tolerate such failures. Effectiveness of the proposed solution is shown through preliminary simulation results.
VARIABLE SELECTION FOR NOISY DATA APPLIED IN PROTEOMICS
2014
International audience; The paper proposes a variable selection method for pro-teomics. It aims at selecting, among a set of proteins, those (named biomarkers) which enable to discriminate between two groups of individuals (healthy and pathological). To this end, data is available for a cohort of individuals: the biological state and a measurement of concentrations for a list of proteins. The proposed approach is based on a Bayesian hierarchical model for the dependencies between biological and instrumental variables. The optimal selection function minimizes the Bayesian risk, that is to say the selected set of variables maximizes the posterior probability. The two main contributions are: (…
Input Selection Methods for Soft Sensor Design: A Survey
2020
Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …
P-FCM: a proximity-based fuzzy clustering for user-centered web applications
2003
Abstract In last years, the Internet and the web have been evolved in an astonishing way. Standard web search services play an important role as useful tools for the Internet community even though they suffer from a certain difficulty. The web continues its growth, making the reliability of Internet-based information and retrieval systems more complex. Nevertheless there has been a substantial analysis of the gap between the expected information and the returned information, the work of web search engine is still very hard. There are different problems concerning web searching activity, one among these falls in the query phase. Each engine provide an interface which the user is forced to le…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery
2018
This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…
Measuring Social Responsibility: A Multicriteria Approach
2016
In this chapter we present a portfolio selection model for Socially Responsible Investment. The model, following the spirit of Socially Responsible Investment, consists of two different steps. Firstly, a social screening is applied in order to obtain the feasible set of assets accomplishing the socially responsible investment policy of the assets’ manager. In this step, an indicator is obtained for the measurement of the social responsibility degree of an asset. Assets are then ranked using this indicator from the most socially responsible to the less socially responsible. In a second step, once the feasible set is obtained, composed of those socially responsible assets verifying the screen…
Gray code for derangements
2004
AbstractWe give a Gray code and constant average time generating algorithm for derangements, i.e., permutations with no fixed points. In our Gray code, each derangement is transformed into its successor either via one or two transpositions or a rotation of three elements. We generalize these results to permutations with number of fixed points bounded between two constants.
How selection of collaborating partners impact on the green performance of global businesses? An empirical study of green sustainability
2020
In recent days, both collaboration and sustainability have become an integral part of many global supply chains to achieve business excellence. Although previous literature and actual practices confirmed the successful implementation of sustainability practices through supply chain collaborations, it is not clear how collaborating partners can support financial and environmental performance, and hence strengthen the partnership performance in the global supply chains. To address this practice-based research question, we test the theoretical underpinning of suppliers and logistics partners in relation to required skills selection. We capture the depth of interdependencies in collaborations f…
Secure and Privacy Preserving Pattern Matching in Distributed Cloud-based Data Storage
2019
Given two strings: pattern $p$ of length $m$ and text $t$ of length $n$ . The string matching problem is to find all (or some) occurrences of the pattern $p$ in the text $t$ . We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.