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    Wyświetlanie 1-6 z 6
    Tytuł:
    EMOT - an evolutionary approach to 3D computer animation
    Autorzy:
    Kwaśnicka, H.
    Woźniak, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/1943270.pdf
    Data publikacji:
    2007
    Wydawca:
    Politechnika Gdańska
    Tematy:
    gene expression programming
    computer animation
    simulation
    motion
    Opis:
    Key-framing and Inverse Kinematics are popular animation methods, but new approaches are still developed. We propose a new evolutionary method of creating animation - the EMOT (Evolutionary MOTion) system. It enables automation of motion of animated characters and uses a new evolutionary approach - Gene Expression Programming (GEP). Characters are controlled by computer programs, an animator providing the way of motion's evaluation. GEP works with a randomly selected initial population, using directed but random selection. Experiments have shown that the proposed method is capable of developing robust controllers.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2007, 11, 1-2; 71-86
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Hash function generation by means of Gene Expression Programming
    Autorzy:
    Varrette, S.
    Muszyński, J.
    Bouvry, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/106148.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
    Tematy:
    hash function
    Gene Expression Programming
    Genetic Programming
    GEPHashSearch
    cryptography
    Opis:
    Cryptographic hash functions are fundamental primitives in modern cryptography and have many security applications (data integrity checking, cryptographic protocols, digital signatures, pseudo random number generators etc.). At the same time novel hash functions are designed (for instance in the framework of the SHA-3 contest organized by the National Institute of Standards and Technology (NIST)), the cryptanalysts exhibit a set of statistical metrics (propagation criterion, frequency analysis etc.) able to assert the quality of new proposals. Also, rules to design "good" hash functions are now known and are followed in every reasonable proposal of a new hash scheme. This article investigates the ways to build on this experiment and those metrics to generate automatically compression functions by means of Evolutionary Algorithms (EAs). Such functions are at the heart of the construction of iterative hash schemes and it is therefore crucial for them to hold good properties. Actually, the idea to use nature-inspired heuristics for the design of such cryptographic primitives is not new: this approach has been successfully applied in several previous works, typically using the Genetic Programming (GP) heuristic [1]. Here, we exploit a hybrid meta-heuristic for the evolutionary process called Gene Expression Programming (GEP) [2] that appeared far more efficient computationally speaking compared to the GP paradigm used in the previous papers. In this context, the GEPHashSearch framework is presented. As it is still a work in progress, this article focuses on the design aspects of this framework (individuals definitions, fitness objectives etc.) rather than on complete implementation details and validation results. Note that we propose to tackle the generation of compression functions as a multi-objective optimization problem in order to identify the Pareto front i.e. the set of non-dominated functions over the four fitness criteria considered. If this goal is not yet reached, the first experimental results in a mono-objective context are promising and open the perspective of fruitful contributions to the cryptographic community.
    Źródło:
    Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2012, 12, 3; 37-53
    1732-1360
    2083-3628
    Pojawia się w:
    Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The On-line Evolutionary Method for Soft Fault Diagnosis in Diode-transistor Circuits
    Autorzy:
    Korzybski, M.
    Ossowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/226980.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    electric circuit diagnosis
    soft faults
    multiple faults
    evolutionary computation
    gene expression programming
    genetic algorithm
    differential evolution
    Opis:
    The paper is devoted to diagnostic method enabling us to perform all the three levels of fault investigations - detection, localization and identification. It is designed for analog diode-transistor circuits, in which the circuit’s state is defined by the DC sources’ values causing elements operating points and the harmonic components with small amplitudes being calculated in accordance with small-signal circuit analysis rules. Geneexpression programming (GEP), differential evolution (DE) and genetic algorithms (GA) are a mathematical background of the proposed algorithms. Time consumed by diagnostic process rises rapidly with the increasing number of possible faulty circuit elements in case of using any of mentioned algorithms. The conncept of using two different circuit models with partly different elements allows us to decrease a number of possibly faulty elements in each circuit because some of possibly faulty elements are absent in one of two investigated circuits.
    Źródło:
    International Journal of Electronics and Telecommunications; 2015, 61, 1; 109-115
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of blast-induced ground vibration using gene expression programming (GEP), artificial neural networks (ANNS), and linear multivariate regression (LMR)
    Autorzy:
    Shakeri, Jamshid
    Shokri, Behshad Jodeiri
    Dehghani, Hesam
    Powiązania:
    https://bibliotekanauki.pl/articles/219872.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    strzałowy
    wibracje podłoża
    kopalnia miedzi Sarcheshmeh
    blasting
    ground vibration
    gene expression programming
    linear multivariate regression
    Sarcheshmeh copper mine
    Opis:
    In this paper, an attempt was made to find out two empirical relationships incorporating linear mul-tivariate regression (LMR) and gene expression programming (GEP) for predicting the blast-induced ground vibration (BIGV) at the Sarcheshmeh copper mine in south of Iran. For this purpose, five types of effective parameters in the blasting operation including the distance from the blasting block, the burden, the spacing, the specific charge, and the charge per delay were considered as the input data while the output parameter was the BIGV. The correlation coefficient and root mean squared error for the LMR were 0.70 and 3.18 respectively, while the values for the GEP were 0.91 and 2.67 respectively. Also, for evaluating the validation of these two methods, a feed-forward artificial neural network (ANN) with a 5-20-1 structure has been used for predicting the BIGV. Comparisons of these parameters revealed that both methods successfully suggested two empirical relationships for predicting the BIGV in the case study. However, the GEP was found to be more reliable and more reasonable.
    Źródło:
    Archives of Mining Sciences; 2020, 65, 2; 317-335
    0860-7001
    Pojawia się w:
    Archives of Mining Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Predicting and minimizing the blasting cost in limestone mines using a combination of gene expression programming and particle swarm optimization
    Autorzy:
    Bastami, Reza
    Bazzazi, Abbas Aghajani
    Shoormasti, Hadi Hamidian
    Ahangari, Kaveh
    Powiązania:
    https://bibliotekanauki.pl/articles/1853861.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    kopalnia wapienia
    wybuch detonacyjny
    regresja nieliniowa
    blasting cost
    limestone mine
    gene expression programming
    non-linear multivariate regression
    particle swarm optimization algorithm
    environmental impacts
    Opis:
    Blasting cost prediction and optimization is of great importance and significance to achieve optimal fragmentation through controlling the adverse consequences of the blasting process. By gathering explosive data from six limestone mines in Iran, the present study aimed to develop a model to predict blasting cost, by gene expression programming method. The model presented a higher correlation coefficient (0.933) and a lower root mean square error (1088) comparing to the linear and nonlinear multivariate regression models. Based on the sensitivity analysis, spacing and ANFO value had the most and least impact on blasting cost, respectively. In addition to achieving blasting cost equation, the constraints such as frag-mentation, fly rock, and back break were considered and analyzed by the gene expression programming method for blasting cost optimization. The results showed that the ANFO value was 9634 kg, hole dia-meter 76 mm, hole number 398, hole length 8.8 m, burden 2.8 m, spacing 3.4 m, hardness 3 Mhos, and uniaxial compressive strength 530 kg/cm2 as the blast design parameters, and blasting cost was obtainedas 6072 Rials/ton, by taking into account all the constraints. Compared to the lowest blasting cost among the 146-research data (7157 Rials/ton), this cost led to a 15.2% reduction in the blasting cost and optimal control of the adverse consequences of the blasting process.
    Źródło:
    Archives of Mining Sciences; 2020, 65, 4; 835-850
    0860-7001
    Pojawia się w:
    Archives of Mining Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Assessment of Los Angeles abrasion value (LAAV) and magnesium sulphate soundness (Mwl) of rock aggregates using gene expression programming and artificial neural networks
    Autorzy:
    Köken, Ekin
    Powiązania:
    https://bibliotekanauki.pl/articles/2203333.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    kruszywa skalne
    sztuczna sieć neuronowa
    siarczan magnezu
    rock aggregates
    aggregate properties
    Los Angeles abrasion loss
    magnesium sulphate soundness
    gene expression programming
    artificial neural network
    Opis:
    It has been acknowledged that two important rock aggregate properties are the Los Angeles abrasion value (LAAV) and magnesium sulphate soundness (M wl). However, the determination of these properties is relatively challenging due to special sampling requirements and tedious testing procedures. In this study, detailed laboratory studies were carried out to predict the LAAV and M wl for 25 different rock types located in NW Turkey. For this purpose, mineralogical, physical, mechanical, and aggregate properties were determined for each rock type. Strong predictive models were established based on gene expression programming (GEP) and artificial neural network (ANN) methodologies. The performance of the proposed models was evaluated using several statistical indicators, and the statistical analysis results demonstrated that the ANN-based proposed models with the correlation of determination (R2) value greater than 0.98 outperformed the other predictive models established in this study. Hence, the ANN-based predictive models can reliably be used to predict the LAAV and M wl for the investigated rock types. In addition, the suitability of the investigated rock types for use in bituminous paving mixtures was also evaluated based on the ASTM D692/D692M standard. Accordingly, most of the investigated rock types can be used in bituminous paving mixtures. In conclusion, it can be claimed that the proposed predictive models with their explicit mathematical formulations are believed to save time and provide practical knowledge for evaluating the suitability of the rock aggregates in pavement engineering design studies in NW Turkey.
    Źródło:
    Archives of Mining Sciences; 2022, 67, 3; 401--422
    0860-7001
    Pojawia się w:
    Archives of Mining Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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