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Theoretical and practical issues related to the applicability of the evaluations of construction project financing having regard to the complexity, timeframe and the limited nature of the resources available have been lately increasingly attracting researchers‘ attention. The assessment of decisions as to the timing and volume of funding of a project is extremely important and relevant for any organisation; therefore, it has been considered necessary to explore different models for possible financing by applying empiric and financial models, as well as theoretical mathematical methods. The objective of the present research exercise was to develop an optimal model for the appropriation of financing of defined scope according to different financing scenarios. For that purpose the researchers used a hypothetical reference heuristic financing appropriation plan for four periods of identical duration in three construction objects. By reference to the linear programming theory an optimal plan was identified by assigning, in individual periods and to each object, different priorities rated in points. The financing appropriation plans are assessed in terms of their impact upon the enterprise value that is computed applying the cash flow discounting method and the tax shield effect theory. Since the selection of the financing source is an important factor for the enterprise value the calculations were performed assessing three possible scenarios of the enterprise financing taking into account the enterprise‘s liquidity: a – an enterprise has accumulated sufficient own funds to finance the project, b– an enterprise has accumulated funds sufficient only to pay the interest for borrowed capital, c – an enterprise does not possess any disposable monetary resources to finance the project during its implementation, therefore it capitalizes the interest payable to the bank. It was concluded that under scenario a the selection of a financing plan does not affect the enterprise value, as the enterprise finances the investment from own resources. In the case of scenario b the loan obtained from the purpose of the investment creates additional value, the choice of the plan, however, does not affect the enterprise value. When capitalising the interest payable to the bank under scenario c, the highest value of an enterprise is created in the case of selection of an optimal plan that is developed by setting an overall limit of the amount to be funded, i.e., by prioritizing mathematical logics without referring to the up-front appropriation of financial resources by objects. The present article deals with the theory of the evaluation of investment project solutions. The results of the evaluation of the solutions for construction project financing appropriation are presented by criteria for optimal solutions and possible financing scenarios. Santrauka Statybos projektų finansavimo vertinimo teorinių ir praktinių pritaikymo klausimų nagrinėjimas, atsižvelgiant į šių projektų įgyvendinimo sudėtingumą, laiką bei reikalingų išteklių ribotumą, pastaruoju metu sulaukia vis didesnio dėmesio. Sprendimų, kiek ir kada finansuoti projektą, vertinimas yra labai svarbus kiekvienai organizacijai, todėl turi būti tiriami įvairūs galimo finansavimo modeliai, taikant empirinius ir finansų bei matematikos teorijos metodus. Tyrimo tikslas – parengti optimalų statybos projekto nurodytos finansavimo apimties paskirstymo modelį pagal skirtingus finansavimo scenarijus. Tyrimui naudotas sąlygiškas euristinis finansavimo paskirstymo planas keturiems vienodos trukmės laikotarpiams pagal tris objektus. Taikant tiesinio programavimo teoriją, optimalus planas randamas kiekvienam objektui konkrečiu periodu suteikus skirtingus balais įvertintus prioritetus. Finansavimo paskirstymo planai vertinami pagal jų įtaką įmonės vertei, kuri skaičiuojama taikant pinigų srautų diskontavimo ir skolinto kapitalo dėl mokesčių sutaupymo papildomai sukuriamos vertės teoriją. Kadangi įmonės vertei svarbus finansavimo šaltinio pasirinkimas, skaičiuota vertinant tris įmonės finansavimo scenarijus atsižvelgiant į įmonės likvidumą:a– įmonė turi sukaupusi pakankamai nuosavų lėšų projektui finansuoti;b– įmonei pakanka nuosavų lėšų tik palūkanoms už skolintas lėšas sumokėti;c– įmonė neturi laisvų piniginių išteklių projekto įgyvendinimo laikotarpiu, todėl kapitalizuoja bankui mokėtinas palūkanas. Nustatyta, kadascenarijaus atveju įmonės vertei finansavimo plano pasirinkimas įtakos nedaro, nes ji investicijas finansuoja nuosavomis lėšomis. Pagalbscenarijų investicijai paimta paskola sukuria papildomą vertę, tačiau plano pasirinkimas įmonės vertės neveikia. Kapitalizuojant bankui mokėtinas palūkanas pagalcscenarijų, didžiausia įmonės vertė sukuriama pasirinkus optimalų planą, kuris sudaromas nurodžius bendrą finansuojamos sumos apribojimą, t. y. suteikiant prioritetą matematinei logikai atsisakius išankstinio finansinių išteklių paskirstymo pagal objektus. Straipsnyje nagrinėjama investicinių projektinių sprendimų vertinimo teorija. Statybos objektų finansavimo paskirstymo vertinimo rezultatai pateikti pagal optimalumo kriterijus ir galimus finansavimo scenarijus. First published online18 Jan 2012 Reikšminiai žodžiai:optimalus modeliavimas,statybos projekto vertinimas,įmonės vertė,investavimo sprendimai,finansavimo alternatyvos

This paper presents three strategic-level models for locating away-from-port storage yards for empty shipping containers. The main objective is to reduce the mileage involved in repositioning empty containers. The models presented attempt to capture the greedy behavior of individual trucking companies and provide for the first time a “user” optimal modeling approach for empty container management. An application to the port complexes of Los Angeles and Long Beach demonstrates that savings associated with storage yards could be easily overestimated when neglecting the perspective of the individual trucking companies. Strategies to encourage system optimal behavior are proposed.

The data-driven optimal modeling and identification of widely-linear quaternion-valued synthetic systems is achieved by using a quaternion-valued gradient based algorithms. To account rigorously for the second-order statistics of the quaternion system, the quaternion least mean square (QLMS) and widely linear quaternion least mean square (WL-QLMS) were selected. The QLMS is shown to successfully model the quaternion-valued systems and the WL-QLMS is able to model both quaternion and widely-linear quaternion valued systems taking into account the full second-order statistics of the system. Analysis has proven that both algorithms are able to adapt to non-stationary nature of the systems. This approach is supported by simulations of various synthetic systems.

In order to improve the accuracy of the area-specific resistance model for direct methanol fuel cell, a heuristic algorithm named cuckoo search is employed. In this work, the optimal modeling strategy is designed to identify the parameters of the area-specific resistance model and minimize the error between the simulation and real experimental data. In experimental evaluation, the proposed algorithm is compared with four heuristic algorithms. The experimental results show the model based on cuckoo search offering better approximation effect and stronger robustness comparing with four other heuristic algorithms.

The consumption of hedonic goods, such as movies or books, involves multisensory, fantasy, and emotive aspects. Hedonic products are often consumed because of symbolic motives. As experience products, hedonic goods involve a high consumption risk for consumers; furthermore, suppliers of hedonic goods face significant competition. Because of these characteristics, hedonic goods have unique diffusion patterns. To provide an overview of these patterns, this article summarizes the current state of research regarding the diffusion of hedonic goods, assesses existing proposed models, and provides guidelines regarding estimating diffusion models. Furthermore, this article explains the influences of special product characteristics on diffusion processes. Results show that flexible diffusion models outperform the well-known Bass model, although the optimal modeling approach differs according to the product. Whereas the diffusion of movies nicely fits Gamma models, the diffusion of music requires more flexible models, such as logistic hazard or mixed Weibull. ACCESS TO FULL TEXT

Following our previous work on optimal modeling of corneal surfaces with Zernike polynomials, we have developed a refined bootstrap-based procedure which improves the accuracy of the previous method. We show that for normal corneas, the optimal number of Zernike terms usually corresponds to the fourth or fifth radial order expansion of Zernike polynomials. On the other hand, for distorted corneas such as those encountered in keratoconus or in surgically altered cases, the estimated model was found to be up to three radial orders higher than for normal corneas.

We present a general modeling approach to crew rostering and its application to computer-assisted generation of rotation-based rosters (or rotas) at the London Underground. Our goals were flexibility, speed, and optimality, and our approach is unique in that it achieves all three. Flexibility was important because requirements at the Underground are evolving and because specialized approaches in the literature did not meet our flexibility-implied need to use standard solvers. We decompose crew rostering into stages that can each be solved with a standard commercial MILP solver. Using a 167 MHz Sun UltraSparc 1 and CPLEX 4.0 MILP solver, we obtained high-quality rosters in runtimes ranging from a few seconds to a few minutes within 2% of optimality. Input data were takes from different depots with crew sizes ranging from 30–150 drivers, i.e., with number of duties ranging from about 200–1000. Using an argument based on decomposition and aggregation, we prove the optimality of our approach for the overall crew rostering problem.

Graph theoretical concepts have been used to model the molecular polarizabilities of fifty-four organic derivatives, and the induced dipole moment of a set of fifty-seven organic compounds divided into three subsets. The starting point of these modeling strategies is the hydrogen-suppressed chemical graph and pseudograph of a molecule, which works very well for second row atoms. From these types of graphs a set of graph-theoretical basis indices, the molecular connectivity indices, can be derived and used to model properties and activities of molecules. With the aid of the molecular connectivity basis indices it is then possible to build higher-order descriptors. The problem of 'graph' encoding the contribution of the inner-core electrons of heteroatoms can here be solved with the aid of odd complete graphs, Kp-(p-odd). The use of these graph tools allow to draw an optimal modeling of the molecular polarizabilities and a satisfactory modeling of the induced dipole moment of a wide set of organic derivatives.

The article presents approaches to the optimal modeling of tax mechanisms in the leveling system of environmental and food security taking into account inter-industry externalities, as well as introduces the indicators of optimal modeling in the course of leveling the negative and positive significant influences on the balance of the ecosystem.

The steelmaking-continuous casting process in modern large steel plant is constituted by several casts, heats, converters, refining furnaces, casters and multiple refining modes. Scheduling problems are solved in existing literatures by two-stage or multi-stage modeling and optimization strategies, but there is no article that investigates the reason why specific strategy is taken. In this paper, the hybrid optimal scheduling model between output variables including device variables (which device) as well as time variables (when to work) and constrains is established on the basis of analyzing intrinsic relationship between the optimized target, constraints and decision variables of scheduling process in a large steel plant of China. In addition, the root cause why the optimization issue cannot be done in one step is described in detail. At the same time, a deep investigate on the reason why two-stage or multi-stage optimization is utilized to solve the schedule problems in the production process that contains multi-converters, multi-refining furnaces and multi-casting machines is carried out, which renders a theory basis for other researchers.

Ecotoxicological management and research have several instruments at their disposal. A discriminatory is made between monitoring of chemical, biochemical, toxicological and ecological parameters, and modeling at a simple, intermediate, and complex level. Their usefulness is discussed and illustrated by examples from the Rhine-Meuse delta. Each type of instrument has its own benefits. In simple cases, application of one instrument will do. More often, however, the objectives set, the compounds concerned, and the species involved require a combination of tools to be used. Chemical and biochemical parameters are oriented around sources and concentrations of well-known priority substances. Toxicological and ecological variables, on the other hand, are directed toward species and the impact of these compounds and other factors as well. In the Rhine-Meuse delta, contamination decreases and more refined instruments are needed to pick out the compounds and species that should get our attention most. An intermediate level of modeling is considered the next logical step after application of simple rules of thumb. © 1997 John Wiley & Sons, Inc. Environ Toxicol Water Qual 12: 321–333, 1997.

Background Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. Methods On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling’s more accuracy for the actual application. Results The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. Conclusions The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system’s further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Since the performance of the clustering scheme is influenced by various factors such as the size or the number of clusters, good models for the clustered sensor networks are necessary to optimize these factors. Hence, determining the optimal number of clusters with the energy consumption has been one of the important issues in the clustered sensor network. Many proposed energy models present the optimal numbers of clusters; however, their accuracy is not satisfactory yet. In this paper, we investigate how to properly derive the perhop distance between the nodes in the multi-hop wireless sensor network. Then, we propose an accurate analytic energy model to derive the optimal number of clusters that minimizes the energy consumption. The simulation results based on the Monte Carlo method show that our model is not only well-matched with the energy consumption by the sensor network, but also more accurate in deriving the optimal number of clusters to maximize the network lifetime.

Sequences of observations or measurements are often modeled as realizations of stochastic processes with some stationary properties in the first and second moments. However in practice, the noise biases and variances are likely to be different for different epochs in time or regions in space, and hence such stationarity assumptions are often questionable. In the case of strict stationarity with equally spaced data, the Wiener-Hopf equations can readily be solved with fast Fourier transforms (FFTs) with optimal computational efficiency. In more general contexts, covariance matrices can also be diagonalized using the Karhunen-Loève transforms (KLTs), or more generally using empirical orthogonal and biorthogonal expansions, which are unfortunately much more demanding in terms of computational efforts. In cases with increment stationarity, the mathematical modeling can be modified and generalized covariances can be used with some computational advantages. The general nonlinear solution methodology is also briefly overviewed with the practical limitations. These different formulations are discussed with special emphasis on the spectral properties of covariance matrices and illustrated with some numerical examples. General recommendations are included for practical geoscience applications.

In a recent article we demonstrated that implicit optimal modeling for shift scheduling (P2) has inherent size and execution time advantages over the general set-covering formulation for shift scheduling (P1) [11, 13]. We postulated that the absence of extraordinary overlap (EO) was a requirement for the equivalence of P1 and P2. We have defined EO as the condition in which the earliest and latest starts for a break in one shift are earlier and later than the earliest and latest starts for a break in any other shift(s). In this article, we prove that our earlier postulate was accurate. Additionally, we discuss research extensions and note other scheduling problems for which implicit modeling may be appropriate. © 1996 John Wiley & Sons, Inc.

Millennia-old Chinese medicine treats disease with many combination therapies involving ingredients used in clinic practice. Fangjiomics is the science of identifying and designing effective mixtures of bioactive agents and elucidating their modes of action beyond those of Chinese patent medicines. Omics profiling and quantitative optimal modeling have been used to associate the various responses with biological pathways related to disease phenotype. Fangjiomics seeks to study myriad compatible combinations that may act through multiple targets, modes of action, and biological pathways balancing on off-target and on-target effects. This approach may lead to the discovery of controllable array-designed therapies to combine less potent elements that are more effective collectively but have fewer adverse side effects than does any element singly.

In order to furthest enhance the whole operation efficiency in group-craft cooperative air combat, this paper presents a new optimal algorithm of airborne ammunition loading scheme based on fighter planes synthesized efficiency index. First, by analyzing the correlative elements of loading scheme optimal modeling of airborne ammunition for group-craft cooperative air combat, an integer nonlinear program mathematic model about ammunition loading scheme is established. Second, this paper designs the six-step algorithm flows of solving the maximum of fighter planes synthesized efficiency index for group-craft cooperative air combat. Last, a simulation experiment shows that, the algorithm is of feasibility and validity, the solving speed is quick (the time is not beyond 10s to solve a 40-variables loading scheme mathematic model), the operation efficiency is high (the synthesized efficiency index of project 2 is higher 23.19 than the traditional project 1’s), which will offer scientific decision-making supports for operation department to constitute the group-craft cooperative air combat loading scheme quickly.

We consider some aspects allowing to optimize the designing of ships with the desired propulsion properties and to estimate the tactical and technicoeconomic characteristics. First question concerns a forecasting of characteristics of flow near hull, including one in boundary layer and viscous wakes, and, above all, a data on water resistance in real conditions. Simulation is carried out in the towing tank with help of the developed methods allowing to reproduce a full-scale experiment with position of description of some hydrodynamic parameters. Also the classification of supercritical regimes of dynamic systems is given and the mechanism of occurrence of self-organization, low-mode chaos and multimode turbulence is predicted. It can be used, in particular, for modeling of ocean processes, in oceanography, etc. We noted the mechanism allowing to approach to the problem of ship moving with substantial decreasing of power inputs in terms of thin coherent formations moving along body. © 2010 IEEE.

This paper is a study of the application of rough set artificial neural networks to the problem of calculating thermal error compensation values for axis positioning on a machine tool. The primary focus is on the development of a rough set approach to reduce a thermal error compensation system which is composed of all of the temperature variables. One modeling of thermal error compensation on machine tools is presented by way of using artificial neural networks integrated rough sets. Positioning error compensation capabilities were tested using industry standard equipment and procedures, and the results obtained is validated for applicability to the problem.

Relation between the possible minimum error (i.e. expectation error) of empirical model and data quality information (e.g., data scale and noise intensity) is analyzed quantitatively, a concept of “restricted optimal model” is proposed, methods to estimate expectation error are introduced, an idea to optimize model using expectation error is proposed. Based on this idea, an optimal Neural Network modeling method is proposed. Its availability and superiority is verified by simulation experiment. Furthermore, a new evaluation index of model, namely error average power (EAP), is proposed, which is suitable to evaluate different modeling methods in simulation experiment.

This chapter contains sections titled: Introduction Classes of Nonlinear Dynamical System Models The de Figueiredo-Dwyer-Zyla Space F Derivation of Sigmoid Functionals Best Robust Approximation of f in the Neural Space N Optimal Combined Structural and Parametric Modeling of Nonlinear Dynamical Systems in N Computationally Intelligent (CI) Systems Concluding Remarks This chapter contains sections titled: References

Spatial information systems contain positional information based on some geodetic reference system. Since any coordinate system is likely to be time dependent as a consequence of datum redefinition...

Implementing Bayesian methods in a model-based closed-loop system requires the integration of a standard response model with a patient-specific response model. This process makes use of specific modeling weights, called Bayesian variances, which determine how the specific model can deviate from the standard model. In this study we applied simulations to select the Bayesian variances yielding the optimal controller for a Bayesian-based closed-loop system for propofol administration using the Bispectral Index (BIS) as a controlled variable.The relevant Bayesian variances determining the modeling process were identified. Each set of such Bayesian variances represents a potential controller. The set, which will result in optimal control, was estimated using calculations on a simulated population. We selected 625 candidate sets. Similar to our previous closed-loop performance study, we applied a simulation protocol to evaluate controller performance. Our population consisted of 416 virtual patients, generated using population characteristics from previous work. A BIS offset trajectory similar to a surgical case was used.We were able to develop, describe, and optimize the parameter setting for a patient-individualized model-based closed-loop controller using Bayesian optimization. Selection of the optimal set yields a controller performing with the following median absolute prediction errors at BIS targets 30, 50, and 70: 12.9 +/- 2.87, 7.59 +/- 0.74, and 5.76 +/- 1.03 respectively.We believe this system can be introduced safely into clinical testing for both induction and maintenance of anesthesia under direct observation of an anesthesiologist.

[1] Water quality evaluation entails both randomness and fuzziness. Two hybrid models are developed, based on the principle of maximum entropy (POME) and engineering fuzzy set theory (EFST). Generalized weighted distances are defined for considering both randomness and fuzziness. The models are applied to 12 lakes and reservoirs in China, and their eutrophic level is determined. The results show that the proposed models are effective tools for generating a set of realistic and flexible optimal solutions for complicated water quality evaluation issues. In addition, the proposed models are flexible and adaptable for diagnosing the eutrophic status.

Environmental risk assessment procedures often use bioaccumulation as a criterion for hazard identification of a polluted location. Field studies regarding metal concentrations in food chains, however, have provided widely different information, because accumulation is shown to vary between the extremes of bioreduction and biomagnification. Bioaccumulation models provide insight regarding species-specific uptake and elimination kinetics of metals and assist in the interpretation of field data. Here, we use the bioaccumulation model OMEGA (Optimal Modeling for Ecotoxicological Applications) to estimate cadmium accumulation in herbivorous voles and carnivorous shrews. In addition to model validation, a meta-analysis of cadmium accumulation data is performed, because earlier studies generally have focused on relationships between cadmium concentrations in either specific tissues (kidney and liver) or whole-body concentrations and total soil levels. Additionally, we included the food-small mammal relationship. Our results show that cadmium whole-body concentrations are significantly related to cadmium levels in food items such as earthworms and plants. In addition, a significant relationship is found between cadmium accumulation in the liver and kidney of small mammals and total soil levels. Cadmium concentrations in shrews typically are an order of magnitude higher than metal levels in voles as a result of higher metal accumulation in earthworms compared to plants. Model predictions for both voles and shrews are in good agreement with field observations; deviations generally are within a factor of five. Small mammals prevent cadmium toxicity by binding this metal to metallothionein, which likely results in low elimination rates. Comparison with empirical elimination rates shows that rate constants of loss are accurately predicted assuming that cadmium is only released via growth dilution. © 2007 SETAC.

A simple disk, representative of a simplied artillery round, was modeled. Several suboptimal modeling techniques were incorporated and compared against optimal modeling techniques to explore the errors introduced. The suboptimal model included wedge elements and an abrupt change in element density. The response to different contact algorithms was also investigated. In addition, the effect of various time steps of the loading curve was also investigated.

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With samples' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

A procedure, based on Sard's generalized spline, for modeling a linear system by an optimal finite-dimensional system is presented. Error bounds are given and the results are illustrated by means of two examples.

The goal of this paper is to present an approach to the problem of the approximation of a complex plant which must to be controlled. Starting from input-output data of the actual system, the proposed procedure leads to determine an optimal reduced model, on which it is very easy to design a min-max control policy for the plant which guarantees a bound of the performance degradation.

Let G(i\omega) be a fixed causal filter. The first result of this paper shows that for any positive integer k and any delay time T > 0 there is an "optimal model" for G(i\omega) out of the class of differential-delay systems of order \leq k (and utilizing delay T ). The second and main result shows that unless G(i\omega) corresponds exactly to a purely differential system of order \leq k then there always exists some delay time T > 0 and corresponding differential-delay system of order \leq k that is a better model for G(i\omega) than even the optimal purely differential system of order \leq k .

The Air Force is using a number of simulation models to perform logistics capability assessment. This paper describes the results of a review of these models, the ultimate goal of which was to develop improved combat operations and logistics capability evaluations. The effort involved investigating the views of current model users and analysts, consulting with subject-matter experts, and reviewing relevant literature and support documentation. From these sources, a set of model evaluation criteria were derived. A methodology based on utility theory is described that can be used to select an optimal modeling system from among several candidate logistics capability assessment modeling systems. Keywords: Air logistics support, Digital simulation, Logistics planning, Mathematical models, Operations research, Utility theory.