Journal articles: 'Continuous random energy model'

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Addario-Berry, Louigi, and Pascal Maillard. "The algorithmic hardness threshold for continuous random energy models." Mathematical Statistics and Learning 2, no. 1 (February 25, 2020): 77–101. http://dx.doi.org/10.4171/msl/12.

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BOVIER, A. "Derrida's Generalized Random Energy models 2: models with continuous hierarchies." Annales de l?Institut Henri Poincare (B) Probability and Statistics 40, no. 4 (August 2004): 481–95. http://dx.doi.org/10.1016/j.anihpb.2003.09.003.

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Ekanga, Trésor. "Multiparticle Localization at Low Energy for Multidimensional Continuous Anderson Models." Advances in Mathematical Physics 2020 (May 5, 2020): 1–15. http://dx.doi.org/10.1155/2020/5270541.

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We study the multiparticle Anderson model in the continuum and show that under some mild assumptions on the random external potential and the inter-particle interaction, for any finite number of particles, the multiparticle lower spectral edges are almost surely constant in absence of ergodicity. We stress that this result is not quite obvious and has to be handled carefully. In addition, we prove the spectral exponential and the strong dynamical localization of the continuous multiparticle Anderson model at low energy. The proof based on the multiparticle multiscale analysis bounds needs the values of the external random potential to be independent and identically distributed, whose common probability distribution is at least Log-Hölder continuous.

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Malyarenko, Anatoliy, and Martin Ostoja-Starzewski. "Fractal planetary rings: Energy inequalities and random field model." International Journal of Modern Physics B 31, no. 30 (December 4, 2017): 1750236. http://dx.doi.org/10.1142/s0217979217502368.

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This study is motivated by a recent observation, based on photographs from the Cassini mission, that Saturn’s rings have a fractal structure in radial direction. Accordingly, two questions are considered: (1) What Newtonian mechanics argument in support of such a fractal structure of planetary rings is possible? (2) What kinematics model of such fractal rings can be formulated? Both challenges are based on taking planetary rings’ spatial structure as being statistically stationary in time and statistically isotropic in space, but statistically nonstationary in space. An answer to the first challenge is given through an energy analysis of circular rings having a self-generated, noninteger-dimensional mass distribution [V. E. Tarasov, Int. J. Mod Phys. B 19, 4103 (2005)]. The second issue is approached by taking the random field of angular velocity vector of a rotating particle of the ring as a random section of a special vector bundle. Using the theory of group representations, we prove that such a field is completely determined by a sequence of continuous positive-definite matrix-valued functions defined on the Cartesian square [Formula: see text] of the radial cross-section [Formula: see text] of the rings, where [Formula: see text] is a fat fractal.

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KÜLSKE, CHRISTOF. "THE CONTINUOUS SPIN RANDOM FIELD MODEL: FERROMAGNETIC ORDERING IN d≥3." Reviews in Mathematical Physics 11, no. 10 (November 1999): 1269–314. http://dx.doi.org/10.1142/s0129055x99000404.

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We investigate the Gibbs-measures of ferromagnetically coupled continuous spins in double-well potentials subjected to a random field (our specific example being the ϕ4 theory), showing ferromagnetic ordering in d≥3 dimensions for weak disorder and large energy barriers. We map the random continuous spin distributions to distributions for an Ising-spin system by means of a single-site coarse-graining method described by local transition kernels. We derive a contour-representation for them with notably positive contour activities and prove their Gibbsianness. This representation is shown to allow for application of the discrete-spin renormalization group developed by Bricmont/Kupiainen implying the result in d≥3.

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Ekanga, Trésor. "Localization in the multi-particle tight-binding Anderson model at low energy." Reviews in Mathematical Physics 32, no. 03 (September 20, 2019): 2050009. http://dx.doi.org/10.1142/s0129055x20500099.

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We consider the multi-particle tight-binding Anderson model and prove that its lower spectral edge is non-random under some mild assumptions on the inter-particle interaction and the random external potential. We also adapt to the low energy regime the multi-particle multi-scale analysis initially developed by Chulaevsky and Suhov in the high disorder limit, if the marginal probability distribution of the i.i.d. random variables is log-Hölder continuous and we obtain the spectral exponential and strong dynamical localization near the bottom of the spectrum.

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ALEINOV, I. D., A. A. MIGDAL, and V. V. ZMUSHKO. "THE ISING MODEL ON THE DYNAMICAL TRIANGULATED RANDOM SURFACE." Modern Physics Letters A 05, no. 10 (April 20, 1990): 787–98. http://dx.doi.org/10.1142/s0217732390000883.

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The critical properties of Ising model on the dynamical triangulated random surface embedded in D-dimensional Euclidean space are investigated. The strong coupling expansion method is used. The transition to thermodynamical limit is performed by means of continuous fractions.

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Huillet, Thierry. "Energy cascades as branching processes with emphasis on Neveu's approach to Derrida's random energy model." Advances in Applied Probability 35, no. 2 (June 2003): 477–503. http://dx.doi.org/10.1239/aap/1051201657.

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Continuous-space-time branching processes (CSBP) are investigated in order to model random energy cascades. CSBPs are based on spectrally positive Lévy processes and, as such, are characterized by their corresponding Laplace exponents. Special emphasis is put on the CSBPs of Feller, Lamperti and Neveu and on their Poisson point process representations. The Neveu model (either supercritical or subcritical) is of particular interest in physics for its connection with the random energy model of Derrida, as revisited by Ruelle. Exploiting some connections between the partition functions of energy and the Poisson-Dirichlet distributions of Pitman and Yor, some information on the zero-temperature limit is extracted. Finally, for the subcritical versions of the three models, we compute the distribution of some of their interesting features: extinction time and probability, area under the profile (total energy) and width (maximal energy).

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Huillet, Thierry. "Energy cascades as branching processes with emphasis on Neveu's approach to Derrida's random energy model." Advances in Applied Probability 35, no. 02 (June 2003): 477–503. http://dx.doi.org/10.1017/s0001867800012349.

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Continuous-space-time branching processes (CSBP) are investigated in order to model random energy cascades. CSBPs are based on spectrally positive Lévy processes and, as such, are characterized by their corresponding Laplace exponents. Special emphasis is put on the CSBPs of Feller, Lamperti and Neveu and on their Poisson point process representations. The Neveu model (either supercritical or subcritical) is of particular interest in physics for its connection with the random energy model of Derrida, as revisited by Ruelle. Exploiting some connections between the partition functions of energy and the Poisson-Dirichlet distributions of Pitman and Yor, some information on the zero-temperature limit is extracted. Finally, for the subcritical versions of the three models, we compute the distribution of some of their interesting features: extinction time and probability, area under the profile (total energy) and width (maximal energy).

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Otunuga, Olusegun M., and Gangaram Ladde. "Two-Scale Network Dynamic Model for Energy Commodity Processes." Journal of Energy 2020 (April 20, 2020): 1–59. http://dx.doi.org/10.1155/2020/2075258.

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In this work, we examine the relationship between different energy commodity spot prices. To do this, multivariate stochastic models with and without external random interventions describing the price of energy commodities are developed. Random intervention process is described by a continuous jump process. The developed mathematical model is utilized to examine the relationship between energy commodity prices. The time-varying parameters in the stochastic model are estimated using the recently developed parameter identification technique called local lagged adapted generalized method of moment (LLGMM). The LLGMM method provides an iterative scheme for updating statistic coefficients in a system of generalized method of moment/observation equations. The usefulness of the LLGMM approach is illustrated by applying to energy commodity data sets for state and parameter estimation problems. Moreover, the forecasting and confidence interval problems are also investigated (U.S. Patent Pending for the LLGMM method described in this manuscript).

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DISTLER, JACQUES, ZVONIMIR HLOUSEK, and HIKARU KAWAI. "HAUSDORFF DIMENSION OF CONTINUOUS POLYAKOV’S RANDOM SURFACES." International Journal of Modern Physics A 05, no. 06 (March 20, 1990): 1093–121. http://dx.doi.org/10.1142/s0217751x90000507.

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In this paper we compute exactly, using the scaling properties of the Liouville theory, the Hausdorff dimension of the continuous random surfaces of Polyakov for D≤1. We find that for D<1, the mean square size of the surface grows as a logarithm of the area of the surface as well as the area of the surface raised to a power, the power being minus the string susceptibility. For D=1 the behavior changes, as expected, because the model undergoes a phase transition. In that case we find that the mean square size of the surface behaves as a combination of terms that grow as a logarithm of the area as well as its square, in qualitative agreement with the results of numerical experiments in discrete models.

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Roberts, J. B., and M. Vasta. "Energy-Based Stochastic Estimation for Nonlinear Oscillators With Random Excitation." Journal of Applied Mechanics 67, no. 4 (August 14, 2000): 763–71. http://dx.doi.org/10.1115/1.1330546.

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A physically based averaging procedure is applied to a general form of a nonlinear single-degree-of-freedom equation, with nonwhite random excitation, leading to a one-dimensional continuous Markov model for the energy envelope. It is demonstrated that, in combination with an energy-based technique for estimating the potential energy function, the Markov model can be used as the basis of a stochastic identification method for estimating the spectrum of the excitation, the static nonlinear restoring characteristic, and the nonlinear damping function, from measurements of the response alone. Moreover it is shown that, by combining results for two levels of stochastic excitation, it is possible to obtain good estimates of damping and stiffness parameters, both linear and nonlinear. [S0021-8936(00)02304-7]

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Han, Changwoon. "Simulation of Series Resistance Increase through Solder Layer Cracking in Si Solar Cells under Thermal Cycling." Energies 16, no. 6 (March 7, 2023): 2524. http://dx.doi.org/10.3390/en16062524.

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In solar cell modules, thermal cycling stresses can cause cracking in the ribbon wire, leading to an increase in series resistance and a drop in the power output of the module. Quantitative analysis was conducted to study the increase in series resistance, considering two cracking models: continuous and random. In the continuous model, it was expected that if all the ribbon wires on the front side of the module cracked, the current would decrease linearly from 0 to 100%, and the series resistance would increase exponentially to infinity. In the random crack model, the current dropped slowly, and the series resistance increased less compared with that in the continuous one. A mathematical model based on the bypass mechanism of the currents was proposed to explain the differences between the two models. The study found that cracking in the solder layer under thermal cycling can be described by a combination of continuous and random models, which can represent the upper and lower levels of the series resistance increase. When the solar cell power dropped to 80%, the increase in series resistance was expected to be in the range of 200 to 250% using the continuous and random models, respectively.

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Bunge, H. J., and E. Dahlem-Klein. "Model Calculations of Continuous Grain Growth in Textured Materials." Textures and Microstructures 13, no. 1 (January 1, 1990): 59–88. http://dx.doi.org/10.1155/tsm.13.59.

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Continuous grain growth of a polycrystalline structure proceeds by the simultaneous movement of all grain boundaries driven by the grain boundary energy and controlled by the boundary mobility. In the present model calculations, energy and mobility are allowed to depend on the orientation difference between neighbouring crystals. The growth process then depends on the misorientation distribution function. In a first approximation the orientation correlations are assumed to be random. Then the MODF can be expressed by the texture. A simple growth model leads to a continuity equation depending on crystal orientation g and grain radius r which can be integrated for the steady state case in which the texture and the shape of the grain size distribution curve remain constant. The same solution also serves as an approximation for pseudo-steady state cases with slowly varying texture. More general solutions are obtained by adding several pseudo-steady state solutions. The specific case of two pseudo-steady state components is considered in detail. Thereby the growth kinetics, texture changes and the form of the grain size distribution curves is obtained.

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Scherbak, L. M., M. Ye Fryz, and V. A. Hotovych. "Electricity consumption simulation using random coefficient periodic autoregressive model." IOP Conference Series: Earth and Environmental Science 1254, no. 1 (October 1, 2023): 012027. http://dx.doi.org/10.1088/1755-1315/1254/1/012027.

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Abstract The concept of a continuous-time conditional linear random process involves a random kernel being integrated stochastically by a process with independent increments, which is often called a “generative process”. In cases where the “generative process” is Poisson, the resulting model represents an investigated signal as a sum of numerous stochastically dependent random impulses each of which occurs according to some inhomogeneous Poisson arrival process. This model can be applied to represent various processes related to energy consumption, such as electricity loads of electrical power systems, gas and water consumption, and other energy resources, while also considering the signals’ cyclostationarity, which is usually caused by the rhythmic nature of consumer behaviour. A member of the discretetime conditional linear cyclostationary random processes class is the random coefficient periodic autoregressive (RCPAR) model, which is appropriate for use in energy informatics, including estimation, forecasting, and computer simulation purposes. The primary objective of the paper is to establish a procedure for simulating the hourly electricity consumption of small and medium-sized enterprises using the RCPAR model, which has periodic parameters and creates cyclostationary properties while also accounting for the investigated process conditional heteroscedasticity. The statistical estimation step of the proposed procedure uses the general methodology for estimating the parameters of the RCPAR model and the methods of statistical analysis of cyclostationary signals. This step is used to identify the simulation characteristics. The simulation step is based on the methods of cyclostationary white noise generation and its transformation by a digital linear filter with random parameters. The last ones are obtained using the Gaussian random vectors computer simulation methods, taking into account the cyclostaionarity property.

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Giraldi, F., and F. Petruccione. "Open System Approach to the Internal Dynamics of a Model Multilevel Molecule." Open Systems & Information Dynamics 19, no. 02 (June 2012): 1250011. http://dx.doi.org/10.1142/s1230161212500114.

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A model multilevel molecule described by two sets of rotational internal energy levels of different parity and degenerate ground states, coupled by a constant interaction, is considered, by assuming that the random collisions in a gas of identical molecules, provoke transitions between adjacent energy levels of the same parity. The prescriptions of the continuous time quantum random walk is applied to the single molecule, interpreted as an open quantum system, and the master equation driving its internal dynamics is built for a general distribution of random collision times. Over estimated long time scales, the dynamics of the coherence terms and the populations of the energy levels is evaluated analytically for relevant classes of non-Poissonian distributions of the collision times. Inverse power law relaxations and the inverse Zeno effect emerge over estimated long time scales and the stable asymptotic equilibrium configuration results to be independent of the distribution of the collision times.

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Baïle, R., J. F. Muzy, and P. Poggi. "Short-term forecasting of surface layer wind speed using a continuous random cascade model." Wind Energy 14, no. 6 (January 17, 2011): 719–34. http://dx.doi.org/10.1002/we.452.

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Maloku, Kaltrina, Benoit Hingray, and Guillaume Evin. "Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model." Hydrology and Earth System Sciences 27, no. 20 (October 18, 2023): 3643–61. http://dx.doi.org/10.5194/hess-27-3643-2023.

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Abstract. Analytical multiplicative random cascades (MRCs) are widely used for the temporal disaggregation of coarse-resolution precipitation time series. This class of models applies scaling models to represent the dependence of the cascade generator on the temporal scale and the precipitation intensity. Although determinant, the dependence on the external precipitation pattern is usually disregarded in the analytical scaling models. Our work presents a unified MRC modelling framework that allows the cascade generator to depend in a continuous way on the temporal scale, precipitation intensity and a so-called precipitation asymmetry index. Different MRC configurations are compared for 81 locations in Switzerland with contrasted climates. The added value of the dependence of the MRC on the temporal scale appears to be unclear, unlike what was suggested in previous works. Introducing the precipitation asymmetry dependence into the model leads to a drastic improvement in model performance for all statistics related to precipitation temporal persistence (wet–dry transition probabilities, lag-n autocorrelation coefficients, lengths of dry–wet spells). Accounting for precipitation asymmetry seems to solve this important limitation of previous MRCs. The model configuration that only accounts for the dependence on precipitation intensity and asymmetry is highly parsimonious, with only five parameters, and provides adequate performances for all locations, seasons and temporal resolutions. The spatial coherency of the parameter estimates indicates a real potential for regionalisation and for further application to any location in Switzerland.

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Verdejo, Humberto, Almendra Awerkin, Wolfgang Kliemann, Cristhian Becker, Héctor Chávez, Karina Barbosa, and José Delpiano. "A Dynamic Stochastic Hybrid Model to Represent Significant Wave Height and Wave Period for Marine Energy Representation." Energies 12, no. 5 (March 7, 2019): 887. http://dx.doi.org/10.3390/en12050887.

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This paper presents a methodology to represent ocean wave power generation based on real data observation for significant wave height (SWH or H s ) and wave period (WP or T). This technique is based on a hybrid model, which considers Fourier series and stochastic differential equations, allowing a continuous time representation of the random changes in the parameters associated with wave power generation ( H s and T). The methodology is explained, including estimation methods and a validation procedure. The data series generated by the models erre used to create simulated wave power output applying a transformed matrix and a theoretical model. The results validate the utilization of this technique, when the objective is to obtain a robust dynamic representation of a random process, oriented to linear studies.

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Franz, Silvio, Flavio Nicoletti, and Federico Ricci-Tersenghi. "Linear low energy excitations in fully-connected models of glasses." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 5 (May 1, 2022): 053302. http://dx.doi.org/10.1088/1742-5468/ac6518.

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Abstract We study the linear excitations around typical energy minima of a mean-field disordered model with continuous degrees of freedom undergoing a random first order transition. Contrary to naive expectations, the spectra of linear excitations are ungapped and we find the presence of a pseudogap corresponding to localized excitations with arbitrary low excitation energy. Moving to deeper minima in the landscape, the excitations appear increasingly localized while their abundance decreases. Beside typical minima, there also exist rare ultra-stable minima, with an energy gap and no localised excitations.

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Sumedha and Mustansir Barma. "Solution of the random field XY magnet on a fully connected graph." Journal of Physics A: Mathematical and Theoretical 55, no. 9 (February 4, 2022): 095001. http://dx.doi.org/10.1088/1751-8121/ac4b8b.

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Abstract We use large deviation theory to obtain the free energy of the XY model on a fully connected graph on each site of which there is a randomly oriented field of magnitude h. The phase diagram is obtained for two symmetric distributions of the random orientations: (a) a uniform distribution and (b) a distribution with cubic symmetry. In both cases, the disorder–averaged ordered state reflects the symmetry of the underlying distribution. The phase boundary has a multicritical point (MCP) which separates a locus of continuous transitions (for small values of h) from a locus of first order transitions (for large h). The free energy is a function of a single variable in case (a) and a function of two variables in case (b), leading to different characters of the MCPs in the two cases. We find that the locus of continuous transitions is given by the same equation for a family of quadriperiodic distributions, which includes the distributions (a) and (b). However, the location of the MCP and the nature of ordered state depend on the form of the distribution. The disorder-averaged ground state energy is found exactly, and the specific heat is shown to approach a constant as temperature approaches zero.

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Fryz, Mykhailo, and Bogdana Mlynko. "Determination of the characteristic function of discrete-time conditional linear random process and its application." Scientific journal of the Ternopil national technical university 109, no. 1 (2023): 16–23. http://dx.doi.org/10.33108/visnyk_tntu2023.01.016.

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The discrete-time conditional linear random process is defined, and its properties in the context of application for mathematical modelling of information signals in energy and medicine are analyzed. The relation to the continuous-time counterpart is considered on the basis of time sampling and aggregation. One-dimensional and multidimensional characteristic functions of discrete-time conditional linear random process are obtained using conditional characteristic function approach. The conditions for the investigated model to be strict sense stationary are justified.

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Kirchberg, Henning, and Abraham Nitzan. "Energy Conversion and Entropy Production in Biased Random Walk Processes—From Discrete Modeling to the Continuous Limit." Entropy 25, no. 8 (August 16, 2023): 1218. http://dx.doi.org/10.3390/e25081218.

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We considered discrete and continuous representations of a thermodynamic process in which a random walker (e.g., a molecular motor on a molecular track) uses periodically pumped energy (work) to pass N sites and move energetically downhill while dissipating heat. Interestingly, we found that, starting from a discrete model, the limit in which the motion becomes continuous in space and time (N→∞) is not unique and depends on what physical observables are assumed to be unchanged in the process. In particular, one may (as usually done) choose to keep the speed and diffusion coefficient fixed during this limiting process, in which case, the entropy production is affected. In addition, we also studied processes in which the entropy production is kept constant as N→∞ at the cost of a modified speed or diffusion coefficient. Furthermore, we also combined this dynamics with work against an opposing force, which made it possible to study the effect of discretization of the process on the thermodynamic efficiency of transferring the power input to the power output. Interestingly, we found that the efficiency was increased in the limit of N→∞. Finally, we investigated the same process when transitions between sites can only happen at finite time intervals and studied the impact of this time discretization on the thermodynamic variables as the continuous limit is approached.

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Abbas, Muhammad Mazhar, Zia Muhammad, Khalid Saleem, Nazar Abbas Saqib, and Hasan Mahmood. "Energy Harvesting and Management in Wireless Networks for Perpetual Operations." Journal of Circuits, Systems and Computers 24, no. 03 (February 10, 2015): 1550041. http://dx.doi.org/10.1142/s0218126615500413.

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Ad hoc wireless networks are self-generating and self-organizing networks consisting of mobile and static nodes, which are small and have limited power resources. In a typical setup, these nodes communicate with each other through wireless medium and may act as source, destination and/or relaying nodes. As the power of the remote nodes is depleted very quickly, it is important to have a renewable energy source to support the network operations and increase lifetime. The availability of energy from the environment is unpredictable, random and uncertain, therefore energy harvesting with appropriate management plays an important role in continuous operations of ad hoc networks. In this paper, an energy harvesting and management model is presented for ad hoc networks. Along with harvesting energy, the proposed model ensures the connectivity requirements of the network for its perpetual operation.

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Yassin, Khaled, Arne Helms, Daniela Moreno, Hassan Kassem, Leo Höning, and Laura J. Lukassen. "Applying a random time mapping to Mann-modeled turbulence for the generation of intermittent wind fields." Wind Energy Science 8, no. 7 (July 13, 2023): 1133–52. http://dx.doi.org/10.5194/wes-8-1133-2023.

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Abstract. A new approach to derive a synthetic wind field model which combines spatial correlations from the Mann model and intermittency is introduced. The term intermittency describes the transition from Gaussian to non-Gaussian velocity increment statistics at small scales, where non-Gaussian velocity increment statistics imply a higher probability for extreme values than a Gaussian distribution. The presented new model is named the Time-mapped Mann model. The intermittency is introduced by applying a special random time-mapping procedure to the regular Mann model. The time-mapping procedure is based on the so-called continuous-time random walk model. As will be shown, the new Time-mapped Mann field reflects spatial correlations from the Mann model in the plane perpendicular to flow direction and temporal intermittency. In the first wind turbine study, the new Time-mapped Mann field and a regular Mann field are used as inflow to a wind turbine in a blade element momentum simulation. It is shown that the wind field intermittency carries over to loads of the wind turbine and, thus, shows the importance of carefully modeling synthetic wind fields.

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Shen, Ke, Toon Pessemier, Xu Gong, Luc Martens, and Wout Joseph. "Genetic Optimization of Energy- and Failure-Aware Continuous Production Scheduling in Pasta Manufacturing." Sensors 19, no. 2 (January 13, 2019): 297. http://dx.doi.org/10.3390/s19020297.

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Energy and failure are separately managed in scheduling problems despite the commonalities between these optimization problems. In this paper, an energy- and failure-aware continuous production scheduling problem (EFACPS) at the unit process level is investigated, starting from the construction of a centralized combinatorial optimization model combining energy saving and failure reduction. Traditional deterministic scheduling methods are difficult to rapidly acquire an optimal or near-optimal schedule in the face of frequent machine failures. An improved genetic algorithm (IGA) using a customized microbial genetic evolution strategy is proposed to solve the EFACPS problem. The IGA is integrated with three features: Memory search, problem-based randomization, and result evaluation. Based on real production cases from Soubry N.V., a large pasta manufacturer in Belgium, Monte Carlo simulations (MCS) are carried out to compare the performance of IGA with a conventional genetic algorithm (CGA) and a baseline random choice algorithm (RCA). Simulation results demonstrate a good performance of IGA and the feasibility to apply it to EFACPS problems. Large-scale experiments are further conducted to validate the effectiveness of IGA.

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Tirone, Salvatore, Maddalena Ghio, Giulia Livieri, Vittorio Giovannetti, and Stefano Marmi. "Kelly Betting with Quantum Payoff: a continuous variable approach." Quantum 5 (September 21, 2021): 545. http://dx.doi.org/10.22331/q-2021-09-21-545.

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The main purpose of this study is to introduce a semi-classical model describing betting scenarios in which, at variance with conventional approaches, the payoff of the gambler is encoded into the internal degrees of freedom of a quantum memory element. In our scheme, we assume that the invested capital is explicitly associated with the quantum analog of the free-energy (i.e. ergotropy functional by Allahverdyan, Balian, and Nieuwenhuizen) of a single mode of the electromagnetic radiation which, depending on the outcome of the betting, experiences attenuation or amplification processes which model losses and winning events. The resulting stochastic evolution of the quantum memory resembles the dynamics of random lasing which we characterize within the theoretical setting of Bosonic Gaussian channels. As in the classical Kelly Criterion for optimal betting, we define the asymptotic doubling rate of the model and identify the optimal gambling strategy for fixed odds and probabilities of winning. The performance of the model are hence studied as a function of the input capital state under the assumption that the latter belongs to the set of Gaussian density matrices (i.e. displaced, squeezed thermal Gibbs states) revealing that the best option for the gambler is to devote all their initial resources into coherent state amplitude.

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Liu, Lifeng, Huisheng Gao, Yuwei Wang, and Wei Sun. "Robust Optimization Model for Photovoltaic Power Producer’s Bidding Decision-Making in Electricity Market." Mathematical Problems in Engineering 2020 (May 30, 2020): 1–8. http://dx.doi.org/10.1155/2020/6109648.

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With the deepening of electricity market (EM) reform and the high penetration of photovoltaic (PV) energy in power system, the uncertainties of a PV power output and fluctuation of EM prices would bring substantial financial risks for PV power producers (PPPs). This paper proposed a robust optimization model for PPP’s power bidding decision-making. Specifically, the random PV power outputs are modeled by the uncertainty set, which need no probabilistic information and can fully depict the continuous range of uncertainties. Subsequently, with respect to any scenario for day-ahead EM prices, PPP’s optimal power bidding strategy is obtained under the worst-case realization within the uncertainty set, which guarantees the robustness in resisting the negative impact of random PV power outputs on PPP’s profit. Moreover, a reformulation approach was introduced for equivalently transforming our model into a tractable framework. Simulation was implemented to validate the feasibility and effectiveness of applying our proposed model.

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Chovancová, Jana, Igor Petruška, and Eva Litavcová. "DEPENDENCE OF CO2 EMISSIONS ON ENERGY CONSUMPTION AND ECONOMIC GROWTH IN THE EUROPEAN UNION: A PANEL THRESHOLD MODEL." Ekonomia i Środowisko - Economics and Environment 78, no. 3 (November 10, 2020): 73–89. http://dx.doi.org/10.34659/2021/3/21.

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This work aims to analyse the dependence of carbon dioxide (CO2) emissions on primary energy consumption at different Gross Domestic Product (GDP) levels in 28 European countries. Data for the years 1995-2019 were used to develop the models. Random Effects, Fixed Effects, a nonlinear panel threshold model and a continuous kink model were used in the panel data analysis. The work shows that the dependence of CO2 emissions on energy consumption varies at different levels of GDP. The model with two threshold values, which determine three modes of behaviour, proves to be the most suitable. As GDP levels increase, the regression coefficient of the dependence of CO2 emissions on energy consumption decreases. Understanding the relationship between these variables is essential for informed and evidence-based decision-making and adopting new or revision of existing energy and climate policies and strategies at the EU and national levels.

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LAYEK, G. C., and SUNITA. "MULTIFRACTAL CASCADE SYMMETRY MODEL FOR FULLY DEVELOPED TURBULENCE." Fractals 26, no. 04 (August 2018): 1850070. http://dx.doi.org/10.1142/s0218348x18500706.

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We report a symmetry model for turbulence intermittency. This is obtained by the compositions of continuous symmetry group transformations of statistical turbulent spectral equation at infinite Reynolds number limit. Flow evolution under group compositions yields velocity structure function exponents that depend on the dilation symmetry group parameter [Formula: see text] [Formula: see text] and a random parameter [Formula: see text]. The random parameter [Formula: see text] is associated with energy distribution. Since the correction to the space-filling Kolmogorov cascade is small, the value of [Formula: see text]. The asymptotic structures are filaments having dimension one, so [Formula: see text] is found to be related with [Formula: see text] by [Formula: see text]. The present model therefore depends only on [Formula: see text], and [Formula: see text] can be ascertained uniquely for [Formula: see text]. It is found that the velocity structure function exponents [Formula: see text], [Formula: see text] in present symmetry model agree well with the existing experimental, direct numerical simulation results and different phenomenological models for [Formula: see text]. For these values of [Formula: see text], the correction to Kolmogorov space-filling, universal [Formula: see text] law, belongs to the range [Formula: see text], and the fractal dimension for the support set lies in [Formula: see text].

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31

Jadhav, Rutuja. "Tracking Locomotion using Reinforcement Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 1777–83. http://dx.doi.org/10.22214/ijraset.2022.45509.

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Abstract: This article presents the concept of reinforcement learning, which prepares a static direct approach for consistent control problems, and adjusts cutting-edge techniques for testing effectiveness in benchmark Mujoco locomotion tasks. This model was designed and developed to use the Mujoco Engine to track the movement of robotic structures and eliminate problems with assessment calculations using perceptron’s and random search algorithms. Here, the machine learning model is trained to make a series of decisions. The humanoid model is considered to be one of the most difficult and ongoing problems to solve by applying state-of-the-art RL technology. The field of machine learning has a great influence on the training model of the RL environment. Here we use random seed values to provide continuous input to achieve optimized results. The goal of this project is to use the Mujoco engine in a specific context to automatically determine the ideal behavior of the robot in an augmented reality environment. Enhanced random search was introduced to train linear guidelines for achieving the efficiency of Mujoco roaming tasks. The results of these models highlight the variability of the Mujoco benchmark task and lead to efficiently optimized rewards

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32

Sablin, Oleg, Dmytro Bosyi, Valeriy Kuznetsov, Konrad Lewczuk, Ivan Kebal, and Sergiy S. Myamlin. "Efficiency of energy storage control in the electric transport systems." Archives of Transport 62, no. 2 (June 30, 2022): 105–22. http://dx.doi.org/10.5604/01.3001.0015.9569.

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The problems of storage and supplying the energy, together with reducing energy intensity for transport, are now crucial for developing sustainable and reliable transport systems. The energy network must be gradually adapted to new loads and power consumption patterns, especially in railways. The article aims to develop the simulation model to investigate the energy storage systems in its use in the electric transport infrastructure. The authors review selected technical solutions for electric energy storage in transport. The theoretical aspects of energy exchange in the energy storage systems were presented as a base for a continuous simulation model of electric transport power supply. In the non-periodic random voltage input applied to the storage unit, it is pro-posed to use the calculation method based on the Duamel integral to analyze its charge-discharge processes. The resistance functions were applied to analyze the traction power supply mode with variable in time and space by active loads. The simulation showed that the direct connection of the unit to the traction network significantly reduces the traction energy consumption.

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Saad, N. Md, M. Z. Sujod, M. I. M. Ridzuan, M. F. Abas, M. S. Jadin, M. S. Bakar, and A. Z. Ahmad. "Solar irradiance uncertainty management based on Monte Carlo-beta probability density function: case in Malaysian tropical climate." Bulletin of Electrical Engineering and Informatics 8, no. 3 (September 1, 2019): 1135–43. http://dx.doi.org/10.11591/eei.v8i3.1581.

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In recent years, solar PV power generation has seen a rapid growth due to environmental benefits and zero fuel costs. In Malaysia, due to its location near the equator, makes solar energy the most utilized renewable energy resources. Unlike conventional power generation, solar energy is considered as uncertain generation sources which will cause unstable energy supplied. The uncertainty of solar resource needs to be managed for the planning of the PV system to produce its maximum power. The statistical method is the most prominent to manage and model the solar irradiance uncertainty patterns. Based on one-minute time interval meteorological data taken in Pekan, Pahang, West Malaysia, the Monte Carlo-Beta probability density function (Beta PDF) is performed to model continuous random variable of solar irradiance. The uncertainty studies are needed to optimally plan the photovoltaic system for the development of solar PV technologies in generating electricity and enhance the utilization of renewable energy; especially in tropical climate region.

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34

Sa’ad, Aisha, Aimé C. Nyoungue, and Zied Hajej. "An Integrated Maintenance Scheduling of a Wind Energy System Minimizing Economic Losses." E3S Web of Conferences 433 (2023): 02007. http://dx.doi.org/10.1051/e3sconf/202343302007.

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The world is faced with a continuous challenge of climate change and global warming as a result of excess carbon emission due to the traditional method of generating electricity from fossil fuels. As measures to curb this challenge, re-searchers explored into renewable energy resources which provide clean and hazard-free energy. Wind as one of the fast-evolving sources requires a lot of attention in generating and sustaining the wind system to ensure reliability and customer satisfaction. In this context, this paper develops a model that forecasts wind energy production by artificial neural network (ANN) method. An integrated model for optimizing the production and maintenance planning cost was developed to minimize economic as well as the production losses that satisfy random demand. Our developed algorithm also determines the minimal number of preventive maintenances to be performed on the turbine thereby evaluating the eco-nomic losses associated with the total production lifecycle.

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35

Kucherov, Ivan. "Modeling Stock Price of Transnational companies using Brownian motion." Artificial societies 17, no. 2 (2022): 0. http://dx.doi.org/10.18254/s207751800019525-6.

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This article is concerned with creating a model for stock price using the Brownian motion. At first, we consider the notion of a discrete time stochastic process, simple random walk, and then move on to its continuous analogue, the Brownian motion. Next we identify the problem with using regular Calculus for stochastic differential equations and derive Ito’s Lemma. After that we derive a model for stock prices and use lognormal distribution to determine its expected value and variance. Finally, we use sample volatility to make predictions for Apple and Gazprom stock prices.

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36

Wang, Yao, Huawei Zhao, Minyao Xu, Chunyang Wu, Jiajia Fu, Lili Gao, and Mahmoud M. A. Kamel. "Numerical Studies on Damage Behavior of Recycled Aggregate Concrete Based on a 3D Model." Materials 13, no. 2 (January 12, 2020): 355. http://dx.doi.org/10.3390/ma13020355.

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This paper develops a 3D base force element method (BFEM) based on the potential energy principle. According to the BFEM, the stiffness matrix and node displacement of any eight-node hexahedral element are derived as a uniform expression. Moreover, this expression is explicitly expressed without a Gaussian integral. A 3D random numerical model of recycled aggregate concrete (RAC) is established. The randomness of aggregate was obtained by using the Monte Carlo random method. The effects of the recycled aggregate substitution and adhered mortar percentage on the elastic modulus and compressive strength are explored under uniaxial compression loading. In addition, the failure pattern is also studied. The obtained data show that the 3D BFEM is an efficient method to explore the failure mechanism of heterogeneous materials. The 3D random RAC model is feasible for characterizing the mesostructure of RAC. Both the substitution of recycled aggregate and the percentage of adhering mortar have a non-negligible influence on the mechanical properties of RAC. As the weak points in the specimen, the old interfacial transition zone (ITZ) and adhered mortar are the major factors that lead to the weakened properties of RAC. The first crack always appears in these weak zones, and then, due to the increase and transfer of stress, approximately two-to-three continuous cracks are formed in the 45°direction of the specimen.

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Hu, Ming, Miao Miao Zhang, Wen Hua Chen, Yong Ping Jin, Guo Ming Xu, Ping Qian, and Jun Pan. "Deploying Impact Dynamics Simulation on Deployable Mechanism of Folding Wing with Clearance." Advanced Materials Research 211-212 (February 2011): 895–99. http://dx.doi.org/10.4028/www.scientific.net/amr.211-212.895.

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Based on the non-linear equivalent spring-damper model in the "two-state model", Impact model with hinge clearance for deployable mechanism of folding wing is set up and deploying dynamics on deployable mechanism of folding wing is simulated including impact force variation caused by the size of clearance and the clearance friction by using ADAMS software. The results show that the random continuous impact force is produced by the influence of clearance; as dimensions of the clearance increase, impact times decrease and amplitudes of impact forces are increased; System energy consumption is speeded up and to some extent times of impacts with clearance and disturbance effects of deployable mechanism is suppressed by friction in the whole deployable process.

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Adhikari, Puja, Mo Xiong, Neng Li, Xiujian Zhao, Paul Rulis, and Wai-Yim Ching. "Structure and Electronic Properties of a Continuous Random Network Model of an Amorphous Zeolitic Imidazolate Framework (a-ZIF)." Journal of Physical Chemistry C 120, no. 28 (July 8, 2016): 15362–68. http://dx.doi.org/10.1021/acs.jpcc.6b06337.

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Girtler, Jerzy. "A Model of Fuel Combustion Process in The Marine Reciprocating Engine Work Space Taking Into Account Load and Wear of Crankshaft-Piston Assembly and The Theory of Semi-Markov Processes." Polish Maritime Research 23, no. 3 (September 1, 2016): 50–57. http://dx.doi.org/10.1515/pomr-2016-0031.

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Abstract The article analyses the operation of reciprocal internal combustion engines, with marine engines used as an example. The analysis takes into account types of energy conversion in the work spaces (cylinders) of these engines, loads of their crankshaft-piston assemblies, and types of fuel combustion which can take place in these spaces during engine operation. It is highlighted that the analysed time-dependent loads of marine internal combustion engine crankshaft-piston assemblies are random processes. It is also indicated that the wear of elements of those assemblies resulting from their load should also be considered a random process. A hypothesis is formulated which explains random nature of load and the absence of the theoretically expected detonation combustion in engines supplied with such fuels as Diesel Oil, Marine Diesel Oil, and Heavy Fuel Oil. A model is proposed for fuel combustion in an arbitrary work space of a marine Diesel engine, which has the form of a stochastic four-state process, discrete in states and continuous in time. The model is based on the theory of semi-Markov processes.

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40

Zhang, Junyi, Hong Sun, Dehua Gao, Lang Qiao, Ning Liu, Minzan Li, and Yao Zhang. "Detection of Canopy Chlorophyll Content of Corn Based on Continuous Wavelet Transform Analysis." Remote Sensing 12, no. 17 (August 24, 2020): 2741. http://dx.doi.org/10.3390/rs12172741.

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The content of chlorophyll, an important substance for photosynthesis in plants, is an important index used to characterize the photosynthetic rate and nutrient grade of plants. The real-time rapid acquisition of crop chlorophyll content is of great significance for guiding fine management and differentiated fertilization in the field. This study used the method of continuous wavelet transform (CWT) to process the collected visible and near-infrared spectra of a corn canopy. This task was conducted to extract the valuable information in the spectral data and improve the sensitivity of chlorophyll content assessment. First, a Savitzky–Golay filter and standard normal variable processing were applied to the spectral data to eliminate the influence of random noise and limit drift on spectral reflectance. Second, CWT was performed on the spectral reflection curve with 10 frequency scales to obtain the wavelet energy coefficient of the spectral data. The characteristic bands related to chlorophyll content in the spectral data and the wavelet energy coefficients were screened using the maximum correlation coefficient and the local correlation coefficient extrema, respectively. A partial least-square regression model was established. Results showed that the characteristic bands selected via local correlation coefficient extrema in a wavelet energy coefficient created a detection model with optimal accuracy. The determination coefficient (Rc2) of the calibration set was 0.7856, and the root-mean-square error (RMSE) of the calibration set (RMSEC) was 3.0408. The determination coefficient (Rv2) of the validation set is was 0.7364, and the RMSE of the validation set (RMSEV) was 3.3032. Continuous wavelet transform is a process of data dimension enhancement which can effectively extract the sensitive variables from spectral datasets and improve the detection accuracy of models.

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41

Li, Lijuan, Yuange Li, Yongdong Chen, Hongliang Liu, and Qingsong Zhang. "Analysis of power system angle stability based on Heun algorithm under gauss and jump excitation." Journal of Physics: Conference Series 2369, no. 1 (November 1, 2022): 012036. http://dx.doi.org/10.1088/1742-6596/2369/1/012036.

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In the process of promoting the dual-carbon goals, the “double-high” character of the power system is gradually becoming obvious and brings a lot of random factors, such as high proportion of new energy access and cut out power system, brings gauss excitation from continuous fluctuations and jump excitation from shock fluctuations, affecting the power system safety operation. Combining the effects of gauss excitation and jump excitation, described as excitation terms acting on gauss white noise and poisson white noise. Constructing the stochastic dynamic model with jump of power system, Heun method is constructed to solve the model, and the comprehensive influence of stochastic excitation and jump excitation under different intensities on stability analysis is analyzed quantitatively. The simulation results of one-machine infinite-bus (OMIB) system shows the correctness and rationality of the method constructed, and provides ideas for the analysis of power system stability under the combined influence of multiple types of random factors.

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Ezzitouni, Jarmouni, Mouhsen Ahmed, Lamhammedi Mohammed, and Krari Ayoub. "Management of battery charging and discharging in a photovoltaic system with variable power demand using artificial neural networks." E3S Web of Conferences 297 (2021): 01037. http://dx.doi.org/10.1051/e3sconf/202129701037.

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The energy is the basis of all human activities. Nowadays, much of the world’s energy demand is taken from fossil fuels. However, fossil fuel reserves are limited. The use of solar photovoltaic energy is therefore a necessity for the future. With the rapid increase of photovoltaic or hybrid systems, solar batteries provide an unforgettable energy storage tool in this type of systems in order to ensure an energy supply to consumers. Due to the sensitivity of solar batteries and the random operation of photovoltaic systems that depend on solar irradiance, control and management strategies are quite important. In this paper, we present a technique based on artificial neural networks to control the charging and discharging of solar batteries in order to protect the batteries from overcharging and deep discharging. In addition, ensuring continuous supply to consumers. The proposed model is developed and simulated in Matlab/Simulink.

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Chen, Jing, Wenqiang Xu, Weimin Peng, and Baixi Xing. "Turning Delay Stochastic User Equilibrium Model based on the Weibull Distribution." PROMET - Traffic&Transportation 30, no. 2 (April 24, 2018): 131–40. http://dx.doi.org/10.7307/ptt.v30i2.2321.

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With the continuous expansion of urban scales and the constant growth of traffic demands, it has become important to accurately predict the distribution of traffic flow so as to relieve the traffic jams and lower the energy consumption. This research mainly focuses on the distribution problem of traffic flow in the urban traffic network. A minimization program has been provided as an alternative formulation for the turning delay stochastic user equilibrium problem. The paper derives the Weibull distribution-based node-link random loading mechanism of turning delay for direct calculation of link and turning flows that are consistent with thepath flow, thus avoiding the enumeration of turning paths. Numerical examples are provided to illustrate the turning delay stochastic user equilibrium (SUE) model and the nodelink- based algorithm. The experiment demonstrates that the present method can reflect the relative performance of link and turning costs well, while presenting its advantages in the simulation of large-scale turning delay flow ssignment.

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44

Zhang, Haiming, Aifeng Tao, Junhao Tu, Junwei Su, and Shuya Xie. "The Focusing Waves Induced by Bragg Resonance with V-Shaped Undulating Bottom." Journal of Marine Science and Engineering 9, no. 7 (June 27, 2021): 708. http://dx.doi.org/10.3390/jmse9070708.

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Intensive wave reflection occurs when the wavelengths of the incident waves and bottom undulations are in a 2:1 ratio. Existing studies have included the Bragg resonance phenomenon of waves passing over a continuous undulating bottom parallel to and oblique to the shoreline. More generally, the Bragg resonance mechanism is used as a means of coastal protection, rather than wave power generation. To focus the wave energy in a specific area, here, we propose sinusoidal sandbars of a horizontal V-shaped pattern, which is formed by two continuous undulating bottoms inclined at an angle to each other and the center axis of the angle is perpendicular to the shoreline. Based on the high-order spectral (HOS) numerical model, both the characteristics of Bragg resonance induced by the regular waves and random waves are investigated. In the scenario of regular waves, it shows that the wave-focusing effect is related to the angle of the V-shaped undulating bottom, and the optimal angle of inclination for the V-shaped undulating bottom is 162.24°. On that basis, considering the interactions between the random waves and the V-shaped undulating bottom of 162.24°, the Bragg resonance characteristics of random waves are studied. The BFI factor combining wave steepness and spectrum width can evaluate the focusing intensity of the Bragg resonance of the random waves. For BFI, in the range of 0.15–1.0, the values of Hsmax/Hs0 linearly increase with the increase of BFI.

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Xu, Lei, and Zhihai Xiang. "A continuous broadband electromagnetic energy harvester based on amplitude and phase adjustments." Smart Materials and Structures 31, no. 3 (February 4, 2022): 035014. http://dx.doi.org/10.1088/1361-665x/ac4ea6.

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Abstract Broadening the bandwidth of vibration energy harvesters is a critical issue for their practical implementations. Although utilizing multi-degree-of-freedoms is a frequently used solution to widen the operating frequency range, the resultant effective bandwidth could consist of discrete peaks (existing local minimum points lower than the half-power level) if the modal amplitudes have large differences at different frequencies. To solve these problems, we designed a new electromagnetic multi-modal energy harvester, which works in a broad and continuous low-frequency bandwidth. This is achieved by attaching the magnet and the coil to a compliant frame integrated with two different kinked beams, respectively. In this way, the voltage can be generated in a continuous and wide frequency range by adjusting the amplitudes and phases of the magnet and the coil in different modes according to a proposed design requirement. Finite element results and experimental results are in good agreement with each other, which validate the performance of the proposed harvester. The experimental results demonstrate that the half-power bandwidth can be achieved in the range of 15.0 Hz and the maximum peak power is 1.56 mW at the center frequency of 40.5 Hz under base excitation of the root-mean-square acceleration of 0.24 g. The broadband and high power density feature are also validated in a random excitation test, so that this harvester has great potential for practical applications.

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46

Delcea, Camelia, Liviu-Adrian Cotfas, Mostafa Salari, and R. Milne. "Investigating the Random Seat Boarding Method without Seat Assignments with Common Boarding Practices Using an Agent-Based Modeling." Sustainability 10, no. 12 (December 5, 2018): 4623. http://dx.doi.org/10.3390/su10124623.

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Research related to creating new and improved airplane boarding methods has seen continuous advancement, in recent years, while most of the airline companies have remained committed to the traditional boarding methods. Among the most-used boarding methods, around the world, are back-to-front and random boarding with and without assigned seats. While the other boarding methods used in practice possess strict rules for passengers’ behavior, random without assigned seats is dependent on the passengers own way of choosing the “best” seats. The aim of this paper is to meticulously model the passengers’ behavior, especially, in random boarding without assigned seats and to test its efficiency in terms of boarding time and interferences, in comparison with the other commonly-adopted methods (random boarding with assigned seats, window-middle-aisle (WilMA), back-to-front, reverse pyramid, etc.). One of the main challenges in our endeavor was the identification of the real human passengers’ way of reasoning, when selecting their seats, and creating a model in which the agents possess preferences and make decisions, as close to those decisions made by the human passengers, as possible. We model their choices based on completed questionnaires from three hundred and eighty-seven human subjects. This paper describes the resulting agent-based model and results from the simulations.

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Li, Yalong, Fan Yang, Wenting Zha, and Licheng Yan. "Combined Optimization Prediction Model of Regional Wind Power Based on Convolution Neural Network and Similar Days." Machines 8, no. 4 (November 20, 2020): 80. http://dx.doi.org/10.3390/machines8040080.

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With the continuous optimization of energy structures, wind power generation has become the dominant new energy source. The strong random fluctuation of natural wind will bring challenges to power system dispatching, so it is necessary to predict wind power. In order to improve the short-term prediction accuracy of regional wind power, this paper proposes a new combination prediction model based on convolutional neural network (CNN) and similar days analysis. Firstly, the least square fitting and batch normalization (BN) are used to preprocess the data, and then the recent historical wind power data set for CNN is established. Secondly, the Pearson correlation coefficient and cosine similarity combination method are utilized to find similar days in the long-term data set, and the prediction model based on similar days is constructed by the weighting method. Finally, based on the particle swarm optimization (PSO) method, a combined forecasting model is established. The results show that the combined model can accurately predict the future short-term wind power curve, and the prediction accuracy is improved to different extents compared to a single method.

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48

Zhang, Beikun, and Liyun Xu. "An improved flower pollination algorithm for solving a Type-II U-shaped assembly line balancing problem with energy consideration." Assembly Automation 40, no. 6 (September 18, 2020): 847–56. http://dx.doi.org/10.1108/aa-07-2019-0144.

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Purpose The increasing energy shortage leads to worldwide attentions. This paper aims to develop a mathematical model and optimization algorithm to solve the energy-oriented U-shaped assembly line balancing problem. Different from most existing works, the energy consumption is set as a major objective. Design/methodology/approach An improved flower pollination algorithm (IFPA) is designed to solve the problem. The random key encoding mechanism is used to map the continuous algorithm into discrete problem. The pollination rules are modified to enhance the information exchange between individuals. Variable neighborhood search (VNS) is used to improve the algorithm performance. Findings The experimental results show that the two objectives are in conflict with each other. The proposed methodology can help manager obtain the counterbalance between them, for the larger size balancing problems, and the reduction in objectives is even more significant. Besides, the experiment results also show the high efficiency of the proposed IFPA and VNS. Originality/value The main contributions of this work are twofold. First, a mathematical model for the U-shaped assembly line balancing problem is developed and the model is dual foci including minimized SI and energy consumption. Second, an IFPA is proposed to solve the problem.

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Marzban, Caren, Robert Tardif, and Scott Sandgathe. "Sensitivity Analysis of the Spatial Structure of Forecasts in Mesoscale Models: Noncontinuous Model Parameters." Monthly Weather Review 148, no. 4 (April 1, 2020): 1717–35. http://dx.doi.org/10.1175/mwr-d-19-0321.1.

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Abstract In a recent work, a sensitivity analysis methodology was described that allows for a visual display of forecast sensitivity, with respect to model parameters, across a gridded forecast field. In that approach, sensitivity was assessed with respect to model parameters that are continuous in nature. Here, the analogous methodology is developed for situations involving noncontinuous (discrete or categorical) model parameters. The method is variance based, and the variances are estimated via a random-effects model based on 2k−p fractional factorial designs and Graeco-Latin square designs. The development is guided by its application to model parameters in the stochastic kinetic energy backscatter scheme (SKEBS), which control perturbations at unresolved, subgrid scales. In addition to the SKEBS parameters, the effect of daily variability and replication (both, discrete factors) are also examined. The forecasts examined are for precipitation, temperature, and wind speed. In this particular application, it is found that the model parameters have a much weaker effect on the forecasts as compared to the effect of daily variability and replication, and that sensitivities, weak or strong, often have a distinctive spatial structure that reflects underlying topography and/or weather patterns. These findings caution against fine-tuning methods that disregard 1) sources of variability other than those due to model parameters, and 2) spatial structure in the forecasts.

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García-Puente, B., A. Rodríguez-Hurtado, M. Santos, and J. E. Sierra-García. "Evaluation of XGBoost vs. other Machine Learning models for wind parameters identification." Renewable Energy and Power Quality Journal 21, no. 1 (July 2023): 388–93. http://dx.doi.org/10.24084/repqj21.334.

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Wind energy is one of the most promising renewable energies. But wind is a quite unstable resource due to its continuous variation and random nature. This uncertainty affects the production cost. Therefore, accurate forecasting of wind and energy is very interesting for energy markets. In this work, we test a recent and powerful intelligent technique, extreme gradient boosting (XGBoost), for wind prediction. The forecasting models of some wind features with XGBoost are compared with Support Vector Regression (SVR), Gaussian Process Regression (GPR) and Neural Networks (NN) models. Specifically, the three features predicted are the active power generated by the turbine, the wind speed, and the wind direction. The results conclude that these techniques are useful for wind and energy forecasting, with XGBoost being the most outstanding one, especially for short-term predictions.

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Journal articles on the topic 'Continuous random energy model'

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