Search results for "Algoritmi"
showing 10 items of 204 documents
Prioritāšu mehānisma izmantošana analītisku algoritmu testēšanā
2017
Darbs veltīts sarežģītu algoritmu izpildes testēšanai sistēmas uzturēšanas laikā. Lietotājam, kurš nav IT speciālists, ir nepieciešams pārliecināties, ka algoritms, veicot datu atlasi un analīzi, korekti tos interpretē, un algoritma aprēķina rezultāts ir pareizs. Darbā tiek apskatīta resursu vadības sistēmas Horizon patēriņa starpības sadales koeficienta analīze. Izveidots algoritma apraksts un blokshēmas. Tiek piedāvāts problēmu atrisināt ar starprezultātu izvadi izmantojot prioritāšu mehānisma palīdzību. Risinājums pielietots patēriņa starpības sadales koeficienta analīzei, atzīmējot starprezultātu izvades punktus atbilstoši noteiktajām prioritātēm. Analizējot klientu pieteikumus, autors …
Kvantu algoritmi bumbu meklēšanas modelī
2016
Viens no uzdevumiem, kurā kvantu datoriem ir priekšrocības, salīdzinot ar klasiskiem datoriem, ir vaicāšanas uzdevums. Šajā uzdevumā ir dota zināma funkcija f, nezināma bitu virkne x, un melnā kaste, ar kuras palīdzību var piekļūt x bitiem. Mērķis ir uzbūvēt f(x) rēķināšanas algoritmu, izmantojot mazu skaitu melnās kastes vaicājumu . Viens no modeļiem tādu algoritmu konstruēšanai ir bumbas meklēšanas modelis. Ar šo modeli ir iespējams iegūt kvantu algoritmus ar zemu vaicājumu skaitu dažiem vaicāšanas uzdevumiem. Šajā darbā šīs modelis ir pielietots dažādām funkcijām f ar mērķi izveidot algoritmus ar mazu vaicājumu skaitu. Iegūtie risinājumi tiek salīdzināti ar risinājumiem, kas izmanto cita…
Feature selection for distance-based regression: An umbrella review and a one-shot wrapper
2023
Feature selection (FS) may improve the performance, cost-efficiency, and understandability of supervised machine learning models. In this paper, FS for the recently introduced distance-based supervised machine learning model is considered for regression problems. The study is contextualized by first providing an umbrella review (review of reviews) of recent development in the research field. We then propose a saliency-based one-shot wrapper algorithm for FS, which is called MAS-FS. The algorithm is compared with a set of other popular FS algorithms, using a versatile set of simulated and benchmark datasets. Finally, experimental results underline the usefulness of FS for regression, confirm…
Compression Methods for Microclimate Data Based on Linear Approximation of Sensor Data
2019
Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based …
ES konkurences tiesību regulējums un pierādīšanas standarts aizliegtu vienošanās lietās, kurās izmantota cenu veidošanas algoritmu programmatūra
2021
Eiropas Komisija ir paudusi uzskatu, ka Eiropas Savienībā tiesību regulējumam ir jābūt vienādam, “likvidējot jebkādu mākslīgu nošķīrumu starp tradicionālo un digitālo tirgu”. Šis maģistra darbs pētī jautājumu, vai Eiropas konkurences tiesības paredz iespēju pierādīt aizliegtas vienošanās, karteļa esamību tad, ja tiek izmantoti viedie cenu algoritmi un nav pierādījumu par tradicionālu komunikāciju starp tirgus dalībniekiem. Analizējot judikatūru par LESD 101 (1) punktu, īpaši pievēršoties lietām, kurās pierādījumi vākti e-vidē, tiek secināts ar kādiem ierobežojumiem būtu jāsastopas izmeklējošajai iestādei, piemēram, EK, mēģinot pierādīt tāda karteļa esamību, kas darbojas uz algoritmu pamata.…
Evolutionary design optimization with Nash games and hybridized mesh/meshless methods in computational fluid dynamics
2012
On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction
2020
Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider an approach using a relatively large tolerance for the Markov chain Monte Carlo sampler to ensure its sufficient mixing, and post-processing the output leading to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators, and propose an adaptive approximate Bayesi…
Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach
2021
Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete graphical criteria and procedures exist for many identification problems, there are still challenging but important extensions that have not been considered in the literature. To tackle these new settings, we present a search algorithm directly over the rules of do-calculus. Due to generality of do-calculus, the search is capable of taking more advanced data-generating mechanisms into account along with an arbitrary type of both observational and…
The Max-Product Algorithm Viewed as Linear Data-Fusion: A Distributed Detection Scenario
2019
In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a distributed hypothesis test conducted by a max-product iteration over a binary-valued pairwise Markov random field and show that the decision variables obtained are linear combinations of the local log-likelihood ratios observed in the network. Then, we use these linear combinations to formulate the system performance in terms of the false-alarm and detection probabilities. Our findings indicate that, in the hypothesis test concerned, the optimal performance of the max-product a…
Surrogate outcomes and transportability
2019
Identification of causal effects is one of the most fundamental tasks of causal inference. We consider an identifiability problem where some experimental and observational data are available but neither data alone is sufficient for the identification of the causal effect of interest. Instead of the outcome of interest, surrogate outcomes are measured in the experiments. This problem is a generalization of identifiability using surrogate experiments and we label it as surrogate outcome identifiability. We show that the concept of transportability provides a sufficient criteria for determining surrogate outcome identifiability for a large class of queries.