Abstract: In this work, the system evaluates the impact of considering a stochastic approach on the day ahead basis Unit Commitment. Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The Unit Commitment model consists in the minimization of the total operation costs considering unit’s technical constraints like ramping rates, minimum up and down time. Load shedding and wind power spilling is acceptable, but at inflated operational costs. The evaluation process consists in the calculation of the optimal unit commitment and in verifying the fulfillment of the considered constraints. For the calculation of the optimal unit commitment, an algorithm based on the Benders Decomposition, namely on the Dual Dynamic Programming, was developed. Two approaches were considered on the construction of stochastic solutions. Data related to wind power outputs from two different operational days are considered on the analysis. Stochastic and deterministic solutions are compared based on the actual measured wind power output at the operational day. Through a technique capability of finding representative wind power scenarios and its probabilities, the system can analyze a more detailed process about the expected final operational cost.
Abstract: Unsatisfactory experiences due to an information shortage regarding the future pay-offs of actual choices, yield satisficing decision-making. This research will examine, for the first time in the literature, the motivation behind suboptimal decisions due to uncertainty by subjecting Adam Smith’s and Jeremy Bentham’s assumptions about the nature of the actions that lead to satisficing behavior, in order to clarify the theoretical background of a “consumption-based satisfactory time” concept. The contribution of this paper with respect to the existing literature is threefold: firstly, it is showed in this paper that Adam Smith’s uncertainty is related to the problem of the constancy of ideas and not related directly to beliefs. Secondly, possessions, as in Jeremy Bentham’s oeuvre, are assumed to be just as pleasing, as protecting and improving the actual or expected quality of life, so long as they reduce any displeasure due to the undesired outcomes of uncertainty. Finally, each consumption decision incurs its own satisfactory time period, owed to not feeling hungry, being healthy, not having transportation…etc. This reveals that the level of satisfaction is indeed a behavioral phenomenon where its value would depend on the simultaneous satisfaction derived from all activities.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: The purpose of the paper is to address the strategic
risk issues surrounding Hindi film distribution in Mumbai for a film
distributor, who acts as an entrepreneur when launching a product
(movie) in the market (film territory).The paper undertakes a
fundamental review of films and risk in the Hindi film industry and
applies Grounded Theory technique to understand the complex
phenomena of risk taking behavior of the film distributors (both
independent and studios) in Mumbai. Rich in-depth interviews with
distributors are coded to develop core categories through constant
comparison leading to conceptualization of the phenomena of
interest. This paper is a first-of-its-kind-attempt to understand risk
behavior of a distributor, which is akin to entrepreneurial risk
behavior under conditions of uncertainty.
Abstract: Market is an important factor for start-ups to look into
during decision-making in product development and related areas.
Emerging country markets are more uncertain in terms of information
availability and institutional supports. The literature review of market
uncertainty reveals the need for identifying factors representing the
market uncertainty. This paper identifies factors for market
uncertainty using Exploratory Factor Analysis (EFA) and confirmed
the number of factor retention using an alternative factor retention
criterion ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups
from all over India participated in the study. This paper concludes
with the factor structure of ‘market uncertainty’ having dimensions of
uncertainty in industry orientation, uncertainty in customer
orientation and uncertainty in marketing orientation.
Abstract: In medical investigations, uncertainty is a major
challenging problem in making decision for doctors/experts to
identify the diseases with a common set of symptoms and also has
been extensively increasing in medical diagnosis problems. The
theory of cross entropy for intuitionistic fuzzy sets (IFS) is an
effective approach in coping uncertainty in decision making for
medical diagnosis problem. The main focus of this paper is to
propose a new intuitionistic fuzzy cross entropy measure (IFCEM),
which aid in reducing the uncertainty and doctors/experts will take
their decision easily in context of patient’s disease. It is shown that
the proposed measure has some elegant properties, which
demonstrates its potency. Further, it is also exemplified in detail the
efficiency and utility of the proposed measure by using a real life
case study of diagnosis the disease in medical science.
Abstract: This paper attempts to define the validity domain of
LSDP (Loop Shaping Design Procedure) controller system, by
determining the suitable uncertainty region, so that linear system be
stable. Indeed the LSDP controller cannot provide stability for any
perturbed system. For this, we will use the gap metric tool that is
introduced into the control literature for studying robustness
properties of feedback systems with uncertainty. A 2nd order electric
linear system example is given to define the validity domain of LSDP
controller and effectiveness gap metric.
Abstract: Established objective and subjective preconditions for
entrepreneurship, forming the business organically related whole, are
the necessary condition of successful entrepreneurial activities.
Objective preconditions for entrepreneurship are developed by
market economy that should stimulate entrepreneurship by allowing
the use of economic opportunities for all those who want to do
business in respective field while providing guarantees to all owners
and creating a stable business environment for entrepreneurs.
Subjective preconditions of entrepreneurship are formed primarily by
personal characteristics of the entrepreneur. These are his properties,
abilities, skills, physiological and psychological preconditions which
may be inherited, inborn or sequentially developed and obtained
during his life on the basis of education and influences of
surrounding environment. The paper is dealing with issues of
objective and subjective preconditions for entrepreneurship and
provides their analysis in view of the current situation in Slovakia. It
presents risks of the business environment in Slovakia that the Slovak
managers considered the most significant in 2014 and defines the
dominant attributes of the entrepreneur in the current business
environment in Slovakia.
Abstract: This work proposes a fuzzy methodology to support
the investment decisions. While choosing among competitive
investment projects, the methodology makes ranking of projects
using the new aggregation OWA operator – AsPOWA, presented in
the environment of possibility uncertainty. For numerical evaluation
of the weighting vector associated with the AsPOWA operator the
mathematical programming problem is constructed. On the basis of
the AsPOWA operator the projects’ group ranking maximum criteria
is constructed. The methodology also allows making the most
profitable investments into several of the project using the method
developed by the authors for discrete possibilistic bicriteria problems.
The article provides an example of the investment decision-making
that explains the work of the proposed methodology.
Abstract: The construction of a new airport or the extension of
an existing one requires massive investments and many times public
private partnerships were considered in order to make feasible such
projects. One characteristic of these projects is uncertainty with
respect to financial and environmental impacts on the medium to long
term. Another one is the multistage nature of these types of projects.
While many airport development projects have been a success, some
others have turned into a nightmare for their promoters.
This communication puts forward a new approach for airport
investment risk assessment. The approach takes explicitly into
account the degree of uncertainty in activity levels prediction and
proposes milestones for the different stages of the project for
minimizing risk. Uncertainty is represented through fuzzy dual theory
and risk management is performed using dynamic programming. An
illustration of the proposed approach is provided.
Abstract: This research investigates the distribution of food
demand for animal food and the optimum amount of that food
production at minimum cost. The data consist of customer purchase
orders for the food of laying hens, price of food for laying hens, cost
per unit for the food inventory, cost related to food of laying hens in
which the food is out of stock, such as fine, overtime, urgent
purchase for material. They were collected from January, 1990 to
December, 2013 from a factory in Nakhonratchasima province. The
collected data are analyzed in order to explore the distribution of the
monthly food demand for the laying hens and to see the rate of
inventory per unit. The results are used in a stochastic linear
programming model for aggregate planning in which the optimum
production or minimum cost could be obtained. Programming
algorithms in MATLAB and tools in Linprog software are used to get
the solution. The distribution of the food demand for laying hens and
the random numbers are used in the model. The study shows that the
distribution of monthly food demand for laying has a normal
distribution, the monthly average amount (unit: 30 kg) of production
from January to December. The minimum total cost average for 12
months is Baht 62,329,181.77. Therefore, the production planning
can reduce the cost by 14.64% from real cost.
Abstract: Software Effort Estimation is the process of estimating the effort required to develop software. By estimating the effort, the cost and schedule required to estimate the software can be determined. Accurate Estimate helps the developer to allocate the resource accordingly in order to avoid cost overrun and schedule overrun. Several methods are available in order to estimate the effort among which soft computing based method plays a prominent role. Software cost estimation deals with lot of uncertainty among all soft computing methods neural network is good in handling uncertainty. In this paper Radial Basis Function Network is compared with the back propagation network and the results are validated using six data sets and it is found that RBFN is best suitable to estimate the effort. The Results are validated using two tests the error test and the statistical test.
Abstract: This paper presents a new nonlinear integral-type sliding surface for synchronizing two different chaotic systems with parametric uncertainty. On the basis of Lyapunov theorem and average dwelling time method, we obtain the control gains of controllers which are derived to achieve chaos synchronization. In order to reduce the gains, the error system is modeled as a switching system. We obtain the sufficient condition drawn for the robust stability of the error dynamics by stability analysis. Then we apply it to guide the design of the controllers. Finally, numerical examples are used to show the robustness and effectiveness of the proposed control strategy.
Abstract: Robust stability and performance are the two most
basic features of feedback control systems. The harmonic balance
analysis technique enables to analyze the stability of limit cycles
arising from a neural network control based system operating over
nonlinear plants. In this work a robust stability analysis based on the
harmonic balance is presented and applied to a neural based control
of a non-linear binary distillation column with unstructured
uncertainty. We develop ways to describe uncertainty in the form of
neglected nonlinear dynamics and high harmonics for the plant and
controller respectively. Finally, conclusions about the performance of
the neural control system are discussed using the Nyquist stability
margin together with the structured singular values of the uncertainty
as a robustness measure.
Abstract: We consider power system expansion planning under
uncertainty. In our approach, integer programming and stochastic
programming provide a basic framework. We develop a multistage
stochastic programming model in which some of the variables are
restricted to integer values. By utilizing the special property of the
problem, called block separable recourse, the problem is transformed
into a two-stage stochastic program with recourse. The electric power
capacity expansion problem is reformulated as the problem with first
stage integer variables and continuous second stage variables. The
L-shaped algorithm to solve the problem is proposed.
Abstract: Supply network management adopts a systematic
and integrative approach to managing the operations and
relationships of various parties in a supply network. The objective
of the manufactures in their supply network is to reduce inventory
costs and increase customer satisfaction levels. One way of doing
that is to synchronize delivery performance. A supply network can
be described by nodes representing the companies and the links
(relationships) between these nodes. Uncertainty in delivery time
depends on type of network relationship between suppliers. The
problem is to understand how the individual uncertainties influence
the total uncertainty of the network and identify those parts of the
network, which has the highest potential for improving the total
delivery time uncertainty.
Abstract: In this research, Forming Limit Diagrams for supertension
sheet metals which are using in automobile industry have
been obtained. The exerted strains to sheet metals have been
measured with four different methods and the errors of each method
have also been represented. These methods have been compared with
together and the most efficient and economic way of extracting of the
exerted strains to sheet metals has been introduced. In this paper total
error and uncertainty of FLD extraction procedures have been
derived. Determination of the measurement uncertainty in extracting
of FLD has a great importance in design and analysis of the sheet
metal forming process.
Abstract: The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.
Abstract: This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.
Abstract: As a vital activity for companies, new product
development (NPD) is also a very risky process due to the high
uncertainty degree encountered at every development stage and the
inevitable dependence on how previous steps are successfully
accomplished. Hence, there is an apparent need to evaluate new
product initiatives systematically and make accurate decisions under
uncertainty. Another major concern is the time pressure to launch a
significant number of new products to preserve and increase the
competitive power of the company. In this work, we propose an
integrated decision-making framework based on neural networks and
fuzzy logic to make appropriate decisions and accelerate the
evaluation process. We are especially interested in the two initial
stages where new product ideas are selected (go/no go decision) and
the implementation order of the corresponding projects are
determined. We show that this two-staged intelligent approach allows
practitioners to roughly and quickly separate good and bad product
ideas by making use of previous experiences, and then, analyze a
more shortened list rigorously.