Patrick Siarry

Patrick Siarry
Université Paris-Est Créteil Val de Marne - Université Paris 12 | UPEC · Laboratoire Images, Signaux et Systèmes Intelligents (LISSI) - EA 3956

Professor

About

522
Publications
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14,718
Citations

Publications

Publications (522)
Article
Full-text available
Home health services arise from the need for hospitals to care for patients and/or dependent persons who, due to special conditions, require hospitalisation and/or care at home. The organisation of this service impacts the quality and cost of health services, which implies the programming of medical and social staff and the design of their daily ro...
Article
Full-text available
Particle Swarm Optimization (PSO) is a population-based metaheuristic belonging to the class of Swarm Intelligence (SI) algorithms. Nowadays, its effectiveness on many hard problems is no longer to be proven. Nevertheless, it is known to be strongly sensitive on the choice of its settings and weak for local search. In this paper, we propose a new a...
Conference Paper
Full-text available
the progressive development of microscopic medical image segmentation is an important step for modern medicine. However, the existing methods are tricky to be applied on real problems. The objective of this paper is to create an algorithmic system, study on image clustering algorithm based on k-means method, the application context aimed at the blo...
Article
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Today, advances in 3D modeling make it possible to identically reproduce objects, animals, humans and even entire scenes. The broad applications concern video games, virtual reality or augmented reality and cinema, for example. In this article, we propose a new method to build a 3D scene directly from several complementary photographs. The position...
Book
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Due to increasing industry 4.0 practices, massive industrial process data is now available for researchers for modelling and optimization. Artificial Intelligence methods can be applied to the ever-increasing process data to achieve robust control against foreseen and unforeseen system fluctuations. Smart computing techniques, machine learning, dee...
Article
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This paper proposes a unique disturbance rejection factor (DRF) based design of direct stable adaptive fuzzy logic controllers (AFLCs) for a class of non‐linear systems with large and fast disturbances. The proposed AFLCs are realized by employing hybrid combinations of Lyapunov theory based local adaptation and harmony search algorithm based globa...
Book
This book highlights recent research on intelligent systems and nature-inspired computing. It presents 62 selected papers from the 19th International Conference on Intelligent Systems Design and Applications (ISDA 2019), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment br...
Book
This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content wil...
Chapter
This chapter tackles a healthcare problem, known as the patient admission scheduling (PAS) problem. PAS is a combinatorial optimization problem that involves assigning patients to beds in specialized rooms and departments depending on their medical requirements as well as their wishes. We present two heuristics based on the Hungarian algorithm, one...
Book
This book highlights recent research on intelligent systems and nature-inspired computing. It presents 130 selected papers from the 19th International Conference on Intelligent Systems Design and Applications (ISDA 2020), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment b...
Chapter
Extracted Haralick’s texture features from bio-images are a very vital task in textured image handling because the main source of information for interpretation of visual and semantic message to a human observer lies in the picture contours, segmented regions, and/or textures. These analyses consist of extracting some characteristic properties and...
Chapter
The station location problem plays an important role for reducing the amount of energy consumption in several logistics companies while identifying the location of the stations and the number of the located stations. In addition, an electric vehicle represents a significant factor to minimize the costs and to reduce the pollution caused by transpor...
Article
Image segmentation is one of the most critical tasks in Magnetic Resonance (MR) images analysis. Since the performance of most current image segmentation methods is suffered by noise and intensity non-uniformity artifact (INU), a precise and artifact resistant method is desired. In this work, we propose a new segmentation method combining a new Hid...
Article
Full-text available
Optimal sizing of analog circuits is a hard and time-consuming challenge. Nowadays, analog designers are more than ever interested in developing solutions for automating such a task. In order to overcome well-known drawbacks of the conventional equation-based and simulation-based sizing techniques, analog designers are being attracted by the so-cal...
Book
This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers,...
Article
Full-text available
A quantum-inspired PSO (QPSO) algorithm for solving reverse emergence is proposed that is a hybridization of the particle swarm optimization (PSO) algorithm and quantum computing principles. For potential applications, we review specific image processing problems including image denoising and edge detection. Taking cellular automata as a modeling t...
Conference Paper
Swarm Intelligence (SI) is a behavior, used first by Beni and Wang, corresponding to a system working with single and self-organized agents, interacting the ones with each other. This operating concept is implemented in many algorithms. Developed by Kennedy, Eberhart and Shi, Particle Swarm Optimization (PSO) is one of them. Its behavior is based o...
Conference Paper
In this paper, we consider the use of a new parallel efficient global optimization algorithm based on the use of the pseudo expected improvement (PEI) criterion, for the optimal design of analog circuits. A comparison with the conventional efficient global optimization algorithm (EGO) is presented. We show, via two analog circuit designs that the p...
Article
In this paper, we present a new multi-objective optimization approach for segmentation of Magnetic Resonance Imaging (MRI) of the human brain. The proposed algorithm not only takes advantages but also solves major drawbacks of two well-known complementary techniques, called fuzzy entropy clustering method and region-based active contour method, usi...
Conference Paper
Full-text available
This paper presents cooperating Cuckoo Search (CS) and Particle Swarm Optimization (PSO) algorithms for MR image segmentation. The problem can be formulated as an optimization problem and the proposed algorithm has been applied to find the best solution. Since image segmentation requires satisfying several criteria, it is important to know how to o...
Article
In this paper, a novel systematic method for the polynomial controllers (denoted as RST controllers) design and tuning is proposed and successfully implemented based on an epsilon-multiobjective particle swarm optimization (ε-MOPSO) algorithm. The ε-domination concept is used to further improve both properties of the non-premature convergence towar...
Chapter
This work is dedicated to the presentation and the analysis of the performance of Maximum a posteriori based Evolutionary Algorithm (MEA). MEA allows a hybridization of set of operators to preserve the diversity during the search. This approach is based on a set of search strategies which are composed of one crossover with one mutation method, resp...
Article
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An efficient covering of the search space is an important issue when dealing with metaheuristics. Sensitivity analysis methods aim at evaluating the influence of each variable of a problem on a model (i.e. objective function) response. Such methods provide knowledge on the function behavior and would be suitable for guiding metaheuristics. To evalu...
Article
To be efficient and reach the best solution, evolutionary algorithms (EAs) are composed of three evolutionary operators: selection, crossover and mutation. Nevertheless, there is no established rule to choose them from a large panel of operators available in the literature. In this paper, a Maximum A Posteriori (MAP) principle based rule is propose...
Chapter
The present paper utilizes covariance matrix adaptation (CMA), an evolution strategy, in conjunction with H∞-based robust control law to design a stable adaptive fuzzy controller for a class of non-linear systems. The objective of the design is to develop a self-adaptive optimal/near optimal fuzzy controller, with guaranteed stability and satisfact...
Article
This article describes a new clustering method for segmentation of Magnetic resonance imaging (MRI) brain images. Currently, when fuzzy clustering is applied to brain image segmentation, there are two main problems to be solved which are: (i) the sensitivity to noise and intensity non-uniformity (INU) artifact; (ii) the trapping into local minima a...
Article
The problems with the design of hybrid micro-grids are system price and service quality. In this paper, we solve these problems by utilizing renewable resources optimally, maintaining State of Charge (SOC) in batteries. The proposed system also defines the lowest rate for power exchanged between the AC/DC micro-grids. Photovoltaic and wind energy a...
Chapter
In this paper, we propose an improvement method for image segmentation problem using particle swarm optimization (PSO) with a new objective function based on kernelization of improved fuzzy entropy clustering algorithm with spatial local information, called PSO-KFECS. The main objective of our proposed algorithm is to segment accurately images by u...
Article
This paper develops a novel particle swarm optimiser algorithm. The focus of this study is how to improve the performance of the classical particle swarm optimisation approach, i.e., how to enhance its convergence speed and capacity to solve complex problems while reducing the computational load. The proposed approach is based on an improvement of...
Article
Full-text available
The present work discusses a novel conceptual formulation of the fractional-order variational framework for retinex, which is a fractional-order partial differential equation (FPDE) formulation of retinex for the multi-scale nonlocal contrast enhancement with texture preserving. The well-known shortcomings of traditional integer-order computation-b...
Conference Paper
Full-text available
In this paper, an improvement method for segmentation of Magnetic Resonance Imaging (MRI) images using particle swarm optimization (PSO) is proposed. We introduce a new objective function, based on kernelization of fuzzy entropy clustering algorithm with local spatial information and bias correction. By utilizing state-of-the-art development of PSO...
Article
Full-text available
Biogeography-based optimization (BBO) is an evolutionary algorithm which is inspired by the migration of species between habitats. Almost 10 years have passed since the first BBO paper was published in 2008. BBO has successfully solved optimization problems in many different domains and has reached a relatively mature state. Considering the signifi...
Article
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The emergence of high-dimensional data requires the design of new optimization methods. Indeed, conventional optimization methods require improvements, hybridization, or parameter tuning in order to operate in spaces of high dimensions. In this paper, we present a new adaptive variant of a pattern search algorithm to solve global optimization probl...
Article
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In the recent years, there has been a growing interest in wireless sensor networks (WSN). Network’s lifetime depends on energy efficiency and load balancing where connectivity is a very important factor. However, such connectivity can be lost due to the failure of some sensor nodes which creates disruptions to the network operations, lead to a reco...
Article
Full-text available
Model-driven engineering (MDE) and search-based software engineering (SBSE) are both relevant approaches to software engineering. MDE aims to raise the level of abstraction in order to cope with the complexity of software systems, while SBSE involves the application of metaheuristic search techniques to complex software engineering problems, reform...
Chapter
In sustainable computing, Intelligent Decision Support Systems (IDSS) has been adopted for prediction, optimization and decision making challenges under variable number constraints based on un-structured data. The traditional systems are lack of efficiency, limited computational ability, inadequate and impreciseness nature of handling sustainable p...
Chapter
Image thresholding is definitely one of the most popular segmentation approaches for extracting objects from the background, or for discriminating objects from objects that have distinct gray-levels. It is typically simple and computationally efficient. It is based on the assumption that the objects can be distinguished by their gray levels.
Book
This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to...
Chapter
Tuning the parameters of any evolutionary algorithm is a very difficult task. In this chapter, we present a new adaptive multi-objective technique which consists of an adaptation of an adaptive particle swarm optimization approach (Tribes) to the multi-objective case. This multi-objective particle swarm optimizer (MOPSO) is characterized for using...
Chapter
The complex structure of the configuration space of a hard optimization problem inspired to draw analogies with physical phenomena, which led three researchers of IBM society — S. Kirkpatrick, C.D. Gelatt, and M.P. Vecchi — to propose in 1982, and to publish in 1983, a new iterative method: the simulated annealing technique Kirkpatrick et al. Scien...
Article
Full-text available
This paper details the Multiobjective Differential Evolution algorithm (MODE) using crowding distance for the sizing of analog circuits. MODE is used to compute the Pareto front of a biobjective optimization problem, namely maximizing the high current cut-off frequency and minimizing the parasitic input resistance of a second generation current con...
Article
Full-text available
This paper addresses to the flowshop scheduling problem with blocking constraints. The objective is to minimize the makespan criterion. We propose a hybrid combinatorial particle swarm optimization algorithm (HCPSO) as resolution technique for solving this problem. At the initialization, different priority rules are exploited. Experimental study an...
Conference Paper
Bimasco - Bioinspired Multi-Agent System for Combinatorial Optimization - consists of an autonomous multi-agent system for solving optimization problems of different classes. This system uses the metaphor of artificial life in which the artificial world represents the search space of a problem, populated by a set of feasible solutions of the proble...
Article
Full-text available
Digital image watermarking is the process of concealing secret information in a digital image for protecting its rightful ownership. Most of the existing block based singular value decomposition (SVD) digital watermarking schemes are not robust to geometric distortions, such as rotation in an integer multiple of ninety degree and image flipping, wh...
Article
Full-text available
In this paper, we improve D. Karaboga's Artificial Bee Colony (ABC) optimization algorithm, by using the sensitivity analysis method described by Morris. Many improvements of the ABC algorithm have been made, with effective results. In this paper, we propose a new approach of random selection in neighborhood search. As the algorithm is running, we...
Chapter
Various events such as the difficulty of constructing new transport’s axes or natural phenomena encourage the Managers of the power systems to operate in their boundary conditions. It results in some unbalanced distribution of loads, provoking thus overloads of some and a reduction of the stability margin of the electrical system. FACTS (Flexible A...
Article
This paper proposes an enhanced Particle Swarm Optimisation (PSO) algorithm and examines its performance. In the proposed PSO approach, PSO is combined with Evolutionary Game Theory to improve convergence. One of the main challenges of such stochastic op-timisation algorithms is the difficulty in the theoretical analysis of the convergence and perf...
Book
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on Swarm Intelligence Based Optimization, ICSIBO 2016, held in Mulhouse, France, in June 2016. The 9 full papers presented were carefully reviewed and selected from 20 submissions. They are centered around the following topics: theoretic...
Article
In this paper, a novel method for the digital two-Degrees-Of-Freedom (2DOF) controller design, called canonical RST structure, is proposed and successfully implemented based on a Multi-Objective Particle Swarm Optimization (MOPSO) approach. This is a polynomial control structure allowing independently the regulation and the tracking of discrete-tim...
Conference Paper
This research paper discusses image registration techniques using two similarity measures, mattes mutual information and mean squares difference, for lung CT scan pairs obtained from the EMPIRE 10 Challenge under Resources in Image Registration. Each metric is then subjected to regular step gradient descent optimisation algorithms and the results c...
Article
Full-text available
We demonstrate here the phase control of the neutral exciton quantum beats in InGaAs/GaAs quantum dots. A longitudinal magnetic field is used as a tuning parameter to change the phase of the oscillations in a deterministic way. This effect arises from the competition between the Zeeman splitting and the electron/hole exchange interaction on the exc...
Conference Paper
Full-text available
PSO-2S is a multi-swarm PSO algorithm using charged particles in a partitioned search space for continuous optimization problems. In order to improve the performance of PSO-2S, this paper proposes a novel variant of this algorithm, called DPSO-2S, which uses the Dclus-ter neighborhood topologies to organize the communication networks between the pa...
Conference Paper
PSO-2S is a multi-swarm PSO algorithm using charged particles in a partitioned search space for continuous optimization problems. In order to improve the performance of PSO-2S, this paper proposes a novel variant of this algorithm, called DPSO-2S, which uses the Dcluster neighborhood topologies to organize the communication networks between the par...
Article
Tuning the parameters of any evolutionary algorithm is considered as a very difficult task. In this paper, we present a new adaptive multi-objective technique which consists of a hybridization between a particular particle swarm optimization approach (Tribes) and tabu search (TS) technique. The main idea behind this hybridization is to combine the...
Conference Paper
Full-text available
This paper is dedicated to design an efficient metaheuristic based on Bayesian approach to solve continuous optimization problems. The proposed approach is based on the use of different search strategies (crossover and mutation) and then selects the best strategy from those possible ones based on the Bayes theorem. The obtained results were compare...
Article
Digital image watermarking is the process of authenticating a digital image by embedding a watermark into it and thereby protecting the image from copyright infringement. This paper proposes a novel robust image watermarking scheme developed in the wavelet domain based on the singular value decomposition (SVD) and artificial bee colony (ABC) algori...
Article
Full-text available
Background: Filter feature selection methods compute molecular signatures by selecting subsets of genes in the ranking of a valuation function. The motivations of the valuation functions choice are almost always clearly stated, but those for selecting the genes according to their ranking are hardly ever explicit. Method: We addressed the computatio...
Chapter
Full-text available
Multi-objective metaheuristics are over and over again used by analog designers. They allow generating a set of non-dominated solutions (i.e. the Pareto front). In this chapter, the authors highlight the fact, via the application of six multi-objective algorithms to the optimization of conflicting performances of four analog and RF circuits, that t...