4 research outputs found
Recommendation system for real estates based on points of interest
The goal of the thesis was to prototype a recommendation system which would advise the user when purchasing immovable property based on vicinity of points of interest. The data used for determining POI's was provided by Monolit d.o.o. while the data for immovable property were obtained from the website nepremicnine.net. The data is then stored in an PostGIS extended PostGreSQL database, which is used for geographical work. The data is then presented using web services with REST technology in a client-server architecture. For the purpose of client we developed a simple web client based on HTML5, JQuery and CSS3 standards. The user can then filter real estate, set the desired type of points of interest, even set weighted parameters determining the final score for each real estate. The system then presents the best scoring real estates on a map together with the points of interest
Senistivity analysis of the evolution of group behaviour model
V naravi lahko sreÄamo veliko razliÄnih oblik skupinskega vedenja kot so jate ptic ali rib, Ärede paÅ”nih živali in roji insektov. Ker je natanÄno modeliranje vedenja živali in njihovega naravnega okolja zelo kompleksno, si pri raziskovanju evolucije skupinskega vedenja pomagamo s poenostavljenimi modeli živali in okolja. Iz njih želimo izluÅ”Äiti zakonitosti, pravila in znanja zakaj in kako do takega vedenja pride. Pri teh modelih raziskovalci najveÄkrat opazujejo lastnosti in znaÄilnosti, kot so na primer, kakÅ”en je prenos informacije med entitetami, kako združevanje v skupino vpliva na obrambo pred plenilci in na hranjenje, kakÅ”ni režimi vedenja se razvijejo ter kakÅ”en je proces odloÄanja skupine glede na razliÄne situacije (oblike habitata, razmerje razliÄnih plenilcev).
V naÅ”i magistrski nalogi smo se odloÄili razÅ”iriti model in analizo, ki so jo opravili DemÅ”ar in sodelavci [doi: 10.1371/journal.pone.0168876, 10.1038/srep39428]. Pri tem smo se osredotoÄili predvsem na to kako oblika habitata, razmerje razliÄnih plenilcev, lokacija pojavitve plenilca in tip simulacijske zanke, vpliva na razvoj Å”tirih razliÄnih režimov vedenja skupine: moÄno usklajeno gibanje, kroženje okoli praznega jedra, neusklajeno prepletanje in režim tranzicije. Za oblike habitata smo poleg že implementiranih kroga in kvadrata, implementirali Å”e obliko neskonÄne mreže in poligona. Pri lokaciji pojavitve plenilca smo poleg pojavitve izven habitata, analizirali Å”e vpliv pojavitve plenilca znotraj habitata. Na koncu smo Å”e primerjali vpliv razliÄnih implementacij asinhrone simulacijske zanke v nasprotju s sinhrono simulacijsko zanko. V primeru razliÄnih simulacijskih zank nas je zanimalo predvsem, ali tudi na naÅ”em modelu držijo zadnje ugotovitve na tem podroÄju, da asinhronost v simulacijski zanki poveÄuje verjetnost za pojav moÄno usklajenega gibanja.In nature we can find various shapes of collective behavior such as flocks of birds, schools of fish, swarms of insects and herds of grazing animals. In research of evolution of group behavior accurate modelling of animal behavior and their natural habitat is to complex therefor we help ourselves with simplified models of animals and their habitats. We try to find different rules, properties and knowledge as to why and how collective behavior came to evolve. In these models, researchers mostly investigate various properties of collective behavior like: transfer of information between entities, benefits of grouping (defense against predators and foraging), group behavior types and group decision-making processes based on different situations (different habitats or ratio of different predators).
In our master thesis we expanded the model and analysis of DemŔar and co-workers [doi: 10.1371/journal.pone.0168876, 10.1038/srep39428]. We were mostly focused on how different shapes of habitats, ratio of different predators, spawn locations of predators and type of simulation loop influence development of four different types of group behavior regimes: polarized, milling, swarming and transition. We implemented two additional habitats, infinite lattice and polygon to add to the set of already implemented circle and square. We also analyzed how spawning predators within living areas differentiates from spawning predators outside of a living area. At the end we also compared the effects of different implementations of asynchronous simulation loop in comparison to synchronized simulation loop. We were especially interested if the latest findings in this field, that asynchronous simulation loop increases the chance for strongly polarized regime to evolve is also true for our model