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Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm / Mehrdad Bijandi in Transactions in GIS, Vol 25 n° 1 (February 2021)  

Public [article]  inTransactions in GIS > Vol 25 n° 1 (February 2021) . - pp 551 - 574 Titre : Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm Type de document : Article/Communication Auteurs : Mehrdad Bijandi, Auteur ; Mohammad Karimi, Auteur ; Bahman Farhadi Bansouleh, Auteur ; Wim van der Knaap, Auteur Année de publication : 2021 Article en page(s) : pp 551 - 574 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] irrigation [Termes descripteurs IGN] optimisation par colonie de fourmis [Termes descripteurs IGN] parcelle agricole [Termes descripteurs IGN] planification [Termes descripteurs IGN] remembrement agricole [Termes descripteurs IGN] surface cultivée [Termes descripteurs IGN] utilisation du sol Résumé : (Auteur) In the process of agricultural land consolidation, the land parcels are optimally redesigned and rearranged in such a way that the dimensions of the resulting parcels are proportional to agricultural criteria such as irrigation discharge, soil texture, and cropping pattern. Besides these criteria, spatial factors like slope, road accessibility, volume of earthwork, and geometrical factors such as size and shape of parcels are also included in the design process of agricultural land partitioning. In this study, a land partitioning model was proposed using a multi‐objective artificial bee colony algorithm (MOABC‐LP) taking into consideration the mentioned factors. Initially, a feasible dimension range of parcels in a block was calculated based on irrigation efficiency. Two partitioning layouts were defined according to the topography and geometry of blocks. The proposed method was applied to a real study area and the results suggest that the land partitioning plan obtained by the MOABC‐LP model, in comparison with a designer's plan, not only makes the shape and size of parcels more compatible with the topographical and agricultural conditions of each block, but also reduces their cut‐and‐fill ratio. Numéro de notice : A2021-210 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12702 date de publication en ligne : 27/10/2020 En ligne : https://doi.org/10.1111/tgis.12702 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97159 [article]

An improved ant colony optimization-based algorithm for user-centric multi-objective path planning for ubiquitous environments / Zohreh Masoumi in Geocarto international, vol 36 n° 2 ([01/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 137 - 154 Titre : An improved ant colony optimization-based algorithm for user-centric multi-objective path planning for ubiquitous environments Type de document : Article/Communication Auteurs : Zohreh Masoumi, Auteur ; John L. Van Genderen, Auteur ; Sadeghi Niaraki Abolghasem, Auteur Année de publication : 2021 Article en page(s) : pp 137 - 154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] gestion des itinéraires [Termes descripteurs IGN] informatique ubiquitaire [Termes descripteurs IGN] méthode heuristique [Termes descripteurs IGN] optimisation par colonie de fourmis [Termes descripteurs IGN] planification [Termes descripteurs IGN] recherche du chemin optimal [Termes descripteurs IGN] réseau routier Résumé : (auteur) One of the important issues in ubiquitous geographic information science (GIS) is designing user-centric path finding algorithms to meet user needs. Mostly, in a route planning problem, the user’s purpose is optimization of two or more objective functions simultaneously. Thus, the problem is a multi-objective problem. In the present study, having considered multi-objective optimization methods in path finding, we developed an algorithm for solving this problem using an improved multi-objective ant colony optimization (ACO) algorithm. Modifications are introduced for various components of the ant colony metaheuristics; specifically, for those associated with the ‘ant decision rule’. The proposed algorithm was tested on the studied network. The results demonstrate that the proposed approach has acceptable settings, repeatability and run time. In addition, one of the important research outputs is a pareto-front which allows the user to select the final path according to the desired priorities. Numéro de notice : A2021-081 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595176 date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595176 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96823 [article]

Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks / Egor Smirrnov in Geo-spatial Information Science, vol 23 n° 4 (December 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 362 - 374 Titre : Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks Type de document : Article/Communication Auteurs : Egor Smirrnov, Auteur ; Sergei Dunaenko, Auteur ; Sergei Kudinov, Auteur Année de publication : 2020 Article en page(s) : pp 362 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] itinéraire piétionnier [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] optimisation par colonie de fourmis [Termes descripteurs IGN] piéton [Termes descripteurs IGN] plan de déplacement urbain [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] sécurité routière [Termes descripteurs IGN] système multi-agents [Termes descripteurs IGN] urbanisme Résumé : (auteur) When arranging the pedestrian infrastructure, one of the most important components that make a tangible contribution to the safety of pedestrians is to organize the safe road crossing. In cities, pedestrians often cross a road in the wrong place due to established routes or inadequate location of crosswalks. Accidents with the participation of pedestrians who crossed the road neglecting the traffic rules, make up a significant part of the total amount of road accidents. In this paper, we propose a method that allows us, on the basis of the results of a computer simulation of pedestrian traffic, to obtain predicted routes for road crossing and to indicate optimal locations for crosswalks that take into account established pedestrian routes and increase their safety. The work describes an extension for the existing AntRoadPlanner simulation algorithm, which searches for and clusters points where pedestrians cross the roadway and suggests locations for new crosswalks. This method was tested on the basis of a comparative simulation of several territories before and after its application, as well as on the basis of a field study of the territories. The developed algorithm can also be used to search for other potentially dangerous places for pedestrians on plans of districts, for example, crossings in places with limited visibility. Numéro de notice : A2020-789 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1847003 date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1847003 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96551 [article]

Multi-factor of path planning based on an ant colony optimization algorithm / Mingchang Wang in Annals of GIS, vol 26 n° 2 (April 2020)  

Public [article]  inAnnals of GIS > vol 26 n° 2 (April 2020) Titre : Multi-factor of path planning based on an ant colony optimization algorithm Type de document : Article/Communication Auteurs : Mingchang Wang, Auteur ; Chunyu Zhu, Auteur ; Fengyan Wang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] classification floue [Termes descripteurs IGN] gestion des itinéraires [Termes descripteurs IGN] optimisation par colonie de fourmis [Termes descripteurs IGN] planification [Termes descripteurs IGN] processus d'analyse hiérarchisée floue [Termes descripteurs IGN] robot Résumé : (auteur) We propose an improved ant colony algorithm for avoiding obstacles in complex static environments that addresses the problems of a single evaluation factor and low path quality of the traditional ant colony algorithm in path planning. The improvements are: 1) a fuzzy planner is constructed according to the comprehensive evaluation method of fuzzy mathematics and the analytic hierarchy process to comprehensively evaluate and determine the impact of environmental factors, 2) the probability selection formula of the ant colony algorithm is optimized, 3) the pheromone update formula is optimized, and 4) the corner system mechanism is introduced as a post-processing method of path optimization to further smooth the path. Results from simulation experiments of the traditional ant colony algorithm were analysed and compared with those of the improved ant colony algorithm, showing that the latter has a stronger path planning ability and higher algorithm efficiency, resulting in a smoother path with a lower negative impact by environmental factors. Thus, the proposed algorithm is expected to provide a computational basis for effective multi-factor path planning in realistic environments, thereby saving human and material resources. Numéro de notice : A2020-320 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2020.1755725 date de publication en ligne : 13/05/2020 En ligne : https://doi.org/10.1080/19475683.2020.1755725 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95186 [article]

A restrictive polymorphic ant colony algorithm for the optimal band selection of hyperspectral remote sensing images / Xiaohui Ding in International Journal of Remote Sensing IJRS, vol 41 n° 3 (15 - 22 janvier 2020)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 41 n° 3 (15 - 22 janvier 2020) . - pp 1093 - 1117 Titre : A restrictive polymorphic ant colony algorithm for the optimal band selection of hyperspectral remote sensing images Type de document : Article/Communication Auteurs : Xiaohui Ding, Auteur ; Shuqing Zhang, Auteur ; Huapeng Li, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1093 - 1117 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] bande spectrale [Termes descripteurs IGN] dimensionnalité [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] jeu de données [Termes descripteurs IGN] optimisation par colonie de fourmis [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] test de performance Résumé : (auteur) With hundreds of spectral bands, the rise of the issue of dimensionality in the classification of hyperspectral images is usually inevitable. In this paper, a restrictive polymorphic ant colony algorithm (RPACA) based band selection algorithm (RPACA-BS) was proposed to reduce the dimensionality of hyperspectral images. In the proposed algorithm, both local and global searches were conducted considering band similarity. Moreover, the problem of falling into local optima, due to the selection of similar band subsets although travelling different paths, was solved by varying the pheromone matrix between ants moving in opposite directions. The performance of the proposed RPACA-BS algorithm was evaluated using three public datasets (the Indian Pines, Pavia University and Botswana datasets) based on average overall classification accuracy (OA) and CPU processing time. The experimental results showed that average OA of RPACA-BS was up to 89.80%, 94.96% and 92.17% for the Indian Pines, Pavia University and Botswana dataset, respectively, which was higher than that of the benchmarks, including the ant colony algorithm-based band selection algorithm (ACA-BS), polymorphic ant colony algorithm-based band selection algorithm (PACA-BS) and other band selection methods (e.g. the ant lion optimizer-based band selection algorithm). Meanwhile, the time consumed by RPACA-BS and PACA-BS were slightly lower than that of ACA-BS but obviously lower than that of other benchmarks. The proposed RPACA-BS method is thus able to effectively enhance the search abilities and efficiencies of the ACA-BS and PACA-BS algorithms to handle the complex band selection issue for hyperspectral remotely sensed images. Numéro de notice : A2020-214 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01431161.2019.1655810 date de publication en ligne : 20/08/2019 En ligne : https://doi.org/10.1080/01431161.2019.1655810 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94899 [article]

An artificial bee colony-based algorithm to automatically create colour schemes for geovisualizations / Mingguang Wu in Cartographic journal (the), Vol 56 n° 2 (May 2019)  

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Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization / Si Song in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

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Hybrid image noise reduction algorithm based on genetic ant colony and PCNN / Chong Shen in The Visual Computer, vol 33 n° 11 (November 2017)  

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Optimal spatial land-use allocation for limited development ecological zones based on the geographic information system and a genetic ant colony algorithm / Nan Mi in International journal of geographical information science IJGIS, vol 29 n° 12 (December 2015)  

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Modèle intégré de description verbale et de représentation spatiale au sein des SIG / David Brosset in Cartes & Géomatique, n° 215 (mars 2013)  

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JFSMA'11, dix-neuvièmes journées francophones sur les systèmes multi-agents / E. Adam (2011)

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Ant intelligence for solving optimal path-covering problems with multi-objectives / X. Li in International journal of geographical information science IJGIS, vol 23 n° 7-8 (july 2009)

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Intelligent GIS for solving high-dimensional site selection problems using ant colony optimization techniques / X. Li in International journal of geographical information science IJGIS, vol 23 n°3-4 (march - april 2009)

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An innovative method to classify remote-sensing images using Ant Colony Optimization / X. Liu in IEEE Transactions on geoscience and remote sensing, vol 46 n° 12 (December 2008)

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A bottom-up approach to discover transition rules of cellular automata using ant intelligence / X. Liu in International journal of geographical information science IJGIS, vol 22 n°11-12 (november 2008)

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