Modern real-world optimization problems are often high dimensional and subject to many constraints. These problems are typically expensive in terms of cost and computational time. In order to optimize such problems, conventional constraintbased solvers require a high number of function evaluations which are not affordable in practice. Employment of fast surrogate models to approximate objective...

The technique of surrogate data has been used as a method to test for membership of particular classes of linear systems. We suggest an obvious extension of this to classes of nonlinear parametric models and demonstrate our methods with respiratory data from sleeping human infants. Although our data are clearly distinct from the different classes of linear systems we are unable to distinguish b...

the study focused on the analysis of production and marketing constraints of tomato among rural farmers in talensi nabdam district of upper east region of ghana.a total of 100 respondents were interviewed using questionnaire. data was analyzed using descriptive statistics to describe the socio economic characteristics of the farmers and kendall’s coefficient of concordance was used to rank the ...

Abstract Financial portfolio managers typically face multi-period optimization tasks such as short-selling or investing at least a particular portion of the in specific industry sector. A common approach to tackle these problems is use constrained Markov decision process (CMDP) methods, which may suffer from sample inefficiency, hyperparameter tuning, and lack guarantees for constraint violatio...

Multi-channel sparse blind deconvolution, or convolutional coding, refers to the problem of learning an unknown filter by observing its circulant convolutions with multiple input signals that are sparse. This finds numerous applications in signal processing, computer vision, and inverse problems. However, it is challenging learn efficiently due bilinear structure observations respect inputs, as...

one of the most remarkable basis of the gravity data inversion is the recognition of sharp boundaries between an ore body and its host rocks during the interpretation step. therefore, in this work, it is attempted to develop an inversion approach to determine a 3d density distribution that produces a given gravity anomaly. the subsurface model consists of a 3d rectangular prisms of known sizes ...

This paper presents a discriminating approach to detecting the existence of underlying determinism in speech phonemes using the surrogate data method. The discrimination is made using a statistical measurement of neighboring trajectory directions. This approach is experimentally verified with both deterministic and stochastic time series and then applied to speech phonemes from the TIMIT databa...

Ethnographic studies in West Africa show that the practice of sending children away to be raised by relatives and nonrelatives is widespread among many ethnic groups. This paper is an attempt to explore the demographic relevance of the practice. The fostering information is obtained from two sources: the responses given by women to the question on children away from home, and by linking all chi...

We introduce a new correlation-based measure of spike timing reliability. Unlike other measures, it does not require the definition of a posteriori "events". It relies on only one parameter, which relates to the timescale of spike timing precision. We test the measure on surrogate data sets with varying amounts of spike time jitter, and missing or additional spikes, and compare it with a widely...

The natural and surrogate key architectures are two competing approaches to specifying keys in relational databases. We analyze the performance of these approaches with respect to the update complexity and the query data and expression complexity. Our results provide new insights into the advantages and disadvantages of both approaches.