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52. Animalism and the vagueness of composition

Creator:
Bělohrad, Radim
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
Animalism, Lockeanism, partial identity, personal iden-tity, supervaluations, and vagueness
Language:
Slovak
Description:
Lockean theories of personal identity maintain that we per-sist by virtue of psychological continuity, and most Lockeans say that we are material things coinciding with animals. Some animalists ar-gue that if persons and animals coincide, they must have the same intrinsic properties, including thinking, and, as a result, there are ‘too many thinkers’ associated with each human being. Further, Lockeans have trouble explaining how animals and persons can be numerically different and have different persistence conditions. For these reasons, the idea of a person being numerically distinct but coincident with an animal is rejected and animalists conclude that we simply are animals. However, animalists face a similar problem when confronted with the vagueness of composition. Animals are entities with vague boundaries. According to the linguistic account of vagueness, the vagueness of a term consists in there being a number of candidates for the denotatum of the vague term. It seems to imply that where we see an animal, there are, in fact, a lot of distinct but overlapping entities with basically the same intrinsic properties, including think-ing. As a result, the animalist must also posit ‘too many thinkers’ where we thought there was only one. This seems to imply that the animalist cannot accept the linguistic account of vagueness. In this paper the author argues that the animalist can accept the linguistic account of vagueness and retain her argument against Lockeanism.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

53. Annual and seasonal discharge prediction in the middle Danube River basin based on a modified TIPS (Tendency, Intermittency, Periodicity, Stochasticity) methodology

Creator:
Stojković, Milan, Plavšić, Jasna, and Prohaska, Stevan
Type:
article, model:article, and TEXT
Subject:
stochastic modelling, annual and seasonal hydrological predictions, TIPS method, and The middle Danube River basin
Language:
Slovak
Description:
The short-term predictions of annual and seasonal discharge derived by a modified TIPS (Tendency, Intermittency, Periodicity and Stochasticity) methodology are presented in this paper. The TIPS method (Yevjevich, 1984) is modified in such a way that annual time scale is used instead of daily. The reason of extracting a seasonal component from discharge time series represents an attempt to identify the long-term stochastic behaviour. The methodology is applied for modelling annual discharges at six gauging stations in the middle Danube River basin using the observed data in the common period from 1931 to 2012. The model performance measures suggest that the modelled time series are matched reasonably well. The model is then used for the short-time predictions for three annual step ahead (2013–2015). The annual discharge predictions of larger river basins for moderate hydrological conditions show reasonable matching with records expressed as the relative error from –8% to +3%. Irrespective of this, wet and dry periods for the aforementioned river basins show significant departures from annual observations. Also, the smaller river basins display greater deviations up to 26% of the observed annual discharges, whereas the accuracy of annual predictions do not strictly depend on the prevailing hydrological conditions.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

54. Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

Creator:
Hojjati, Ali, Monadi, Mohsen, Faridhosseini, Alireza, and Mohammadi, Mirali
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
NSGA-II, MOPSO, multi-objective optimization, flood control, and hydropower
Language:
Slovak
Description:
Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

55. Application of passive capillary samplers in water stable isotope investigations of snowmelt - a case study from Slovenia

Creator:
Vreča, Polona, Brenčič, Mihael, and Torkar, Anja
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
snowmelt, passive capillary sampler, oxygen and hydrogen isotopes, balanced hierarchical sampling design, ANOVA, and Slovenia
Language:
Slovak
Description:
In this paper we describe the use of modified passive capillary samplers (PCSs) to investigate the water isotope variability of snowmelt at selected sites in Slovenia during winter 2011/2012 and during winter 2012/2013. First, PCS with 3 fibreglass wicks covering approximately 1 m2 were tested to determine sample variability. We observed high variability in the amount of snowmelt water collected by individual wick (185 to 345 g) and in the isotope composition of oxygen (δ18O −10.43‰ to −9.02‰) and hydrogen (δ2H −70.5‰ to −63.6‰) of the collected water. Following the initial tests, a more detailed investigation was performed in winter 2012/2013 and the variability of snowmelt on the local scale among the different levels (i.e. within group, between the close and more distant groups of wicks) was investigated by applying 30 fibreglass wicks making use of Analysis Of Variance (ANOVA) and a balanced hierarchical sampling design. The amount of snowmelt water collected by an individual wick during the whole experiment was between 116 and 1705 g, while the isotope composition varied from −16.32‰ to −12.86‰ for δ18O and from −120.2‰ to −82.5‰ for δ2H. The main source of variance (80%) stems from the variability within the group of wicks (e.g. within group) while other sources contribute less than 20% of the variability. Amount weighted samples for the 2012–2013 season show no significant differences among groups, but significant differences for particular sampling events were observed. These investigations show that due to the variability within the group of wicks, a large number of wicks (> 5) are needed to sample snowmelt.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

56. Applying statistical methods in knowledge management of a multiagent system

Creator:
Košinár, Michal and Kohut, Ondřej
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
knowledge, rules, facts, TIL, TIL-Script, Transparent Intensional Logic, PROLOG, Multiagent Systems, content language, FIPA, a priori probability, conditional probability, and Bayesians probability
Language:
Slovak
Description:
Multi-agent system is a system of autonomous, intelligent but resource-bounded agents. Particular agents have to be able to make decisions on their own, based on the activities of other agents and events within the system as well as in its environment. To this end agents make use of their own internal knowledge base which serves them as a memory. In this paper we focus on the design and management of such a knowledge base. After a brief description of some classical fundamental approaches to the knowledge base management, we propose an improvement based on the application of statistical methods. We focus in particular on the optimization of the process., Multi-agent systém je systém autonomních, inteligentních, ale zdrojově omezených agentů. Konkrétní agenti musí být schopni sami rozhodovat na základě činností jiných agentů a událostí v systému i v jeho prostředí. K tomuto účelu agenti využívají vlastní interní znalostní základnu, která jim slouží jako paměť. V tomto příspěvku se zaměřujeme na návrh a správu takové znalostní báze. Po stručném popisu některých klasických základních přístupů k řízení znalostní báze navrhujeme zlepšení založené na aplikaci statistických metod. Zaměřujeme se především na optimalizaci procesu., and Michal Košinár ; Ondřej Kohut
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public

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