542 research outputs found
On gradual-impulse control of continuous-time Markov decision processes with multiplicative cost
In this paper, we consider the gradual-impulse control problem of
continuous-time Markov decision processes, where the system performance is
measured by the expectation of the exponential utility of the total cost. We
prove, under very general conditions on the system primitives, the existence of
a deterministic stationary optimal policy out of a more general class of
policies. Policies that we consider allow multiple simultaneous impulses,
randomized selection of impulses with random effects, relaxed gradual controls,
and accumulation of jumps. After characterizing the value function using the
optimality equation, we reduce the continuous-time gradual-impulse control
problem to an equivalent simple discrete-time Markov decision process, whose
action space is the union of the sets of gradual and impulsive actions
CHATBOT APPLICATION AS SUPPORT TOOL FOR THE LEARNING PROCESS OF BASIC CONCEPTS OF TELECOMMUNICATIONS AND WIRELESS NETWORKS
There are several applications for Chatbots in education, as well as their contributions to mentoring in the learning process. Bots can assist teachers with staying up to date on new standards and evaluation methodologies. Bots can assist students in understanding tough subjects in a way that makes it appear as if they are being taught by another person. Chatbots serve as virtual assistants in the educational setting, improving efficiency or answering frequently asked questions. In this case, we work on the premise of investigating the potential of Chatbots as analytical tools for analyzing preferred types of learning material in a mobile learning environment, which leads to the acquisition of a proper level of knowledge on the topics of telecommunication and wireless networks
LABOR ADJUSTMENT AND GRADUAL REFORM: IS COMMITMENT IMPORTANT?
We analyze a model in which a government uses a second best policy to affect the reallocation of labor, following a change in relative prices. We consider two extreme cases, in which the government has either unlimited or negligible ability to commit to future actions. We explain why the ability to make commitments may be unimportant, and we illustrate this conjecture with numerical examples. For either assumption about commitment ability, the equilibrium policy involves gradual liberalization. The dying sector is protected during the transition to a free market, in order to decrease the amount of unemployment Our results are sensitive to the assumptions about migration.adjustment costs, dynamic tariffs, time inconsistency, Markov perfection, Labor and Human Capital,
Conceptual hydrological model calibration using multi-objective optimization techniques over the transboundary Komadugu-Yobe basin, Lake Chad Area, West Africa
Study Area: The discharge of the transboundary Komadugu-Yobe Basin, Lake Chad Area, West Africa is calibrated using multi-objective optimization techniques. Study focus: The GR5J hydrological model parameters are calibrated using six optimization methods i.e. Local Optimization-Multi Start (LOMS), the Differential Evolution (DE), the Multiobjective Particle the Swarm Optimization (MPSO), the Memetic Algorithm with Local Search Chains (MALS), the Shuffled Complex Evolution-Rosenbrock’s function (SCE-R), and the Bayesian Markov Chain Monte Carlo (MCMC) approach. Three combined objective functions i.e. Root Mean Square Error, Nash- Sutcliffe efficiency, Kling-Gupta efficiency are applied. The calibration process is divided into two separate episodes (1974–2000 and 1980–1995) so as to ascertain the robustness of the calibration approaches. Runoff simulation results are analysed with a timefrequency wavelet transform. New hydrological insights for the region: For calibration and validation stages, all optimization methods simulate the base flow and high flow spells with a satisfactory level of accuracy. For calibration period, MCMC underestimate it by -0.07 mm/day. The performance evaluation shows that MCMC has the highest values of mean absolute error (0.28) and mean square error (0.40) while LOMS and MCMC record a low volumetric efficiency of 0.56. In all cases, the DE and the SCE-R methods perform better than others. The combination of multi-objective functions and multi-optimization techniques improve the model’s parameters stability and the algorithms’ optimization to represent the runoff in the basin
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