Search results for: stochastic uncertainty analysis

Authors: Nayera E. El-Gharably, Khaled S. El-Kilany, Aziz E. El-Sayed

Abstract:

A key element of many distribution systems is the routing and scheduling of vehicles servicing a set of customers. A wide variety of exact and approximate algorithms have been proposed for solving the vehicle routing problems (VRP). Exact algorithms can only solve relatively small problems of VRP, which is classified as NP-Hard. Several approximate algorithms have proven successful in finding a feasible solution not necessarily optimum. Although different parts of the problem are stochastic in nature; yet, limited work relevant to the application of discrete event system simulation has addressed the problem. Presented here is optimization using simulation of VRP; where, a simplified problem has been developed in the ExtendSimTM simulation environment; where, ExtendSimTM evolutionary optimizer is used to minimize the total transportation cost of the problem. Results obtained from the model are very satisfactory. Further complexities of the problem are proposed for consideration in the future.

Keywords: Discrete event system simulation, optimization using simulation, vehicle routing problem.

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Authors: Ali Salehipour

Abstract:

After presenting the theory of calendar function of Iran-s cross-vaults especially “Niasar" cross-vault in recent years, there has been lots of doubts and uncertainty about this theory by astrologists and archaeologists. According to this theory “Niasar cross-vault and other cross-vaults of Iran has calendar function and are constructed in a way that sunrise and sunset can be seen from one of its openings in the beginning and middle of each season of year". But, mentioning historical documentaries we conclude here that the theory of calendar function of Iran-s cross-vaults does not have any strong basis and individual cross-vaults had only religious function in Iran.

Keywords: cross-vault, fire temple, Calendar function, Sassanid period

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Authors: Swanti Satsangi, Ashish Gulati, Prem Kumar Kalra, C. Patvardhan

Abstract:

Due to the non- intuitive nature of Quantum algorithms, it becomes difficult for a classically trained person to efficiently construct new ones. So rather than designing new algorithms manually, lately, Genetic algorithms (GA) are being implemented for this purpose. GA is a technique to automatically solve a problem using principles of Darwinian evolution. This has been implemented to explore the possibility of evolving an n-qubit circuit when the circuit matrix has been provided using a set of single, two and three qubit gates. Using a variable length population and universal stochastic selection procedure, a number of possible solution circuits, with different number of gates can be obtained for the same input matrix during different runs of GA. The given algorithm has also been successfully implemented to obtain two and three qubit Boolean circuits using Quantum gates. The results demonstrate the effectiveness of the GA procedure even when the search spaces are large.

Keywords: Ancillas, Boolean functions, Genetic algorithm, Oracles, Quantum circuits, Scratch bit

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Authors: Ilaria Lucrezia Amerise

Abstract:

Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.

Keywords: Forecasting problem, interval forecasts, time series, electricity prices, reg-plus-SARMA methods.

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Authors: Alireza Mortezaei, Kimia Mortezaei

Abstract:

Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.

Keywords: Seismic evaluation, FRP, neural network, near-fault ground motion

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Authors: Justinian Anatory

Abstract:

power-line networks are promise infrastructure for broadband services provision to end users. However, the network performance is affected by stochastic channel changing which is due to load impedances, number of branches and branched line lengths. It has been proposed that multi-carrier modulations techniques such as orthogonal frequency division multiplexing (OFDM), Multi-Carrier Spread Spectrum (MC-SS), wavelet OFDM can be used in such environment. This paper investigates the performance of different indoor topologies of power-line networks that uses MC-SS modulation scheme.It is observed that when a branch is added in the link between sending and receiving end of an indoor channel an average of 2.5dB power loss is found. In additional, when the branch is added at a node an average of 1dB power loss is found. Additionally when the terminal impedances of the branch change from line characteristic impedance to impedance either higher or lower values the channel performances were tremendously improved. For example changing terminal load from characteristic impedance (85 .) to 5 . the signal to noise ratio (SNR) required to attain the same performances were decreased from 37dB to 24dB respectively. Also, changing the terminal load from channel characteristic impedance (85 .) to very higher impedance (1600 .) the SNR required to maintain the same performances were decreased from 37dB to 23dB. The result concludes that MC-SS performs better compared with OFDM techniques in all aspects and especially when the channel is terminated in either higher or lower impedances.

Keywords: Communication channel model; Broadband Powerlinecommunication; Branched network; OFDM; Delay Spread, MCSS;impulsive noise; load impedance

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Authors: Tomoaki Hashimoto

Abstract:

In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research fields. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method for unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with unknown probability distribution.

Keywords: Optimal control, stochastic systems, discrete-time systems, probabilistic constraints.

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

In this paper, the problem of stability criteria for Markovian jumping BAM neural networks with leakage and discrete delays has been investigated. Some new sufficient condition are derived based on a novel Lyapunov-Krasovskii functional approach. These new criteria based on delay partitioning idea are proved to be less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, one numerical example is given to illustrate the the usefulness and feasibility of the proposed main results.

Keywords: Stability, Markovian jumping neural networks, Timevarying delays, Linear matrix inequality.

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: Optimal control, ensemble Kalman Filter, topography reconstruction, data assimilation, shallow water equations.

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Authors: Igor Astrov, Mikhail Pikkov

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.

Keywords: Autonomous underwater vehicles, multirate systems, neurocontrollers, situational awareness.

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Authors: Andre A. Keller

Abstract:

The optimal control is one of the possible controllers for a dynamic system, having a linear quadratic regulator and using the Pontryagin-s principle or the dynamic programming method . Stochastic disturbances may affect the coefficients (multiplicative disturbances) or the equations (additive disturbances), provided that the shocks are not too great . Nevertheless, this approach encounters difficulties when uncertainties are very important or when the probability calculus is of no help with very imprecise data. The fuzzy logic contributes to a pragmatic solution of such a problem since it operates on fuzzy numbers. A fuzzy controller acts as an artificial decision maker that operates in a closed-loop system in real time. This contribution seeks to explore the tracking problem and control of dynamic macroeconomic models using a fuzzy learning algorithm. A two inputs - single output (TISO) fuzzy model is applied to the linear fluctuation model of Phillips and to the nonlinear growth model of Goodwin.

Keywords: fuzzy control, macroeconomic model, multiplier - accelerator, nonlinear accelerator, stabilization policy.

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Authors: Omid Jadidi, Fatemeh Firouzi, Enzo Bagliery

Abstract:

Supplier selection, in real situation, is affected by several qualitative and quantitative factors and is one of the most important activities of purchasing department. Since at the time of evaluating suppliers against the criteria or factors, decision makers (DMS) do not have precise, exact and complete information, supplier selection becomes more difficult. In this case, Grey theory helps us to deal with this problem of uncertainty. Here, we apply Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to evaluate and select the best supplier by using interval fuzzy numbers. Through this article, we compare TOPSIS with some other approaches and afterward demonstrate that the concept of TOPSIS is very important for ranking and selecting right supplier.

Keywords: TOPSIS, fuzzy number, MADM, Supplier selection

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Authors: Aparna Viswanath

Abstract:

Electricity spot prices are highly volatile under optimal generation capacity scenarios due to factors such as nonstorability of electricity, peak demand at certain periods, generator outages, fuel uncertainty for renewable energy generators, huge investments and time needed for generation capacity expansion etc. As a result market participants are exposed to price and volume risk, which has led to the development of risk management practices. This paper provides an overview of risk management practices by market participants in electricity markets using financial derivatives.

Keywords: Financial Derivatives, Forward, Futures, Options, Risk Management.

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Authors: D. Kubiliute

Abstract:

The Republic of Lithuania is known as a trusted location for global business institutions and it attracts investors with its competitive environment for financial service providers. Along with the aspiration to offer a strong results-oriented and innovations-driven environment for financial service providers, Lithuanian regulatory authorities consistently implement the European Union's high regulatory standards for financial activities including sustainability-related disclosures. Since the European Union directed its policy towards transition to a climate-neutral, green, competitive and inclusive economy, additional regulatory requirements for financial market participants are adopted: disclosure of sustainable activities, transparency, prevention of greenwashing, and other. The financial sector is one of the key factors influencing the implementation of sustainability objectives in the European Union policies and mitigating the negative effects of climate change – public funds are not enough to make a significant impact on sustainable investments, therefore directing public and private capital to green projects may help to finance the necessary changes. The topic of the study is original and has not yet been widely analyzed in Lithuanian legal discourse. There are used quantitative and qualitative methodologies, logical, systematic and critical analysis principles, hence the aim of this study is to reveal the problematic of the implementation of regulation on sustainability in the Lithuanian financial sector. Additional regulatory requirements could cause serious changes in financial business operations: additional funds, employees and time have to be dedicated in order the companies could implement these regulations. Lack of knowledge and data on how to implement new regulatory requirements towards sustainable reporting causes a lot of uncertainty for financial market participants. And for some companies it might even be an essential point in terms of business continuity. It is considered that the supervisory authorities should find a balance between financial market needs and legal regulation.

Keywords: Financial, market participant, legal, regulation, sustainability.

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Authors: Leszek Chybowski, Artur Bejger, Katarzyna Gawdzińska

Abstract:

Subversion analysis is a tool used in the TRIZ (Theory of Inventive Problem Solving) methodology. This article introduces the history and describes the process of subversion analysis, as well as function analysis and analysis of the resources, used at the design stage when generating possible undesirable situations. The article charts the course of subversion analysis when applied to a fuel injection nozzle of a marine engine. The work describes the fuel injector nozzle as a technological system and presents principles of analysis for the causes of a cracked tip of the nozzle body. The system is modelled with functional analysis. A search for potential causes of the damage is undertaken and a cause-and-effect analysis for various hypotheses concerning the damage is drawn up. The importance of particular hypotheses is evaluated and the most likely causes of damage identified.

Keywords: Complex technical system, fuel injector, function analysis, importance analysis, resource analysis, sabotage analysis, subversion analysis, TRIZ.

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Authors: M. F. Omar, R. A. Salam, R. Abdullah, N. A. Rashid

Abstract:

Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.

Keywords: Simulated annealing, genetic algorithm, sequence alignment, multiple sequence alignment.

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Authors: Adam Niewiadomski

Abstract:

Political transition of agricultural properties in Poland and the former German Democratic Republic (GDR) after 1989 had to include not only Reprivatization but also the issue of returning the properties in kind to their former owners. Restitution in kind applied in GDR to all forms of ownership which were subject to expropriation between 1933 and 1989 except for properties taken over during Soviet occupation in 1945-49. This issue was one of the flashpoints during the process of ownership changes. Privatization, limited as it was, took place in unequal legal environment where only one group of owners was privileged. Executing restitution in kind created a feeling of uncertainty among potential real estate buyers.

Keywords: Reprivatization, agricultural properties, German Democratic Republic, Privatization

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Authors: L. Bennaceur Farah, I. R. Farah, R. Bennaceur, Z. Belhadj, M. R. Boussema

Abstract:

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Keywords: Remote sensing, rough surfaces, inverse problems, SAR, radar scattering, Neural networks and Fractals.

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Authors: Amin Abedi, Naser Vosoughi, Mohammad Bagher Ghofrani

Abstract:

Double heterogeneity of randomly located pebbles in the core and Coated Fuel Particles (CFPs) in the pebbles are specific features in pebble bed reactors and usually, because of difficulty to model with MCNP code capabilities, are neglected. In this study, characteristics of HTR-10, Tsinghua University research reactor, are used and not only double heterogeneous but also truncated CFPs and Pebbles are considered.Firstly, 8335 CFPs are distributed randomly in a pebble and then the core of reactor is filled with those pebbles and graphite pebbles as moderator such that 57:43 ratio of fuel and moderator pebbles is established.Finally, four different core configurations are modeled. They are Simple Cubic (SC) structure with truncated pebbles,SC structure without truncated pebble, and Simple Hexagonal(SH) structure without truncated pebbles and SH structure with truncated pebbles. Results like effective multiplication factor (Keff), critical height,etc. are compared with available data.

Keywords: Double Heterogeneity, HTR-10, MCNP, Pebble Bed Reactor, Stochastic Geometry.

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Authors: Ali Haroonabadi, Mohammad Teshnehlab

Abstract:

None of the processing models in the software development has explained the software systems performance evaluation and modeling; likewise, there exist uncertainty in the information systems because of the natural essence of requirements, and this may cause other challenges in the processing of software development. By definition an extended version of UML (Fuzzy- UML), the functional requirements of the software defined uncertainly would be supported. In this study, the behavioral description of uncertain information systems by the aid of fuzzy-state diagram is crucial; moreover, the introduction of behavioral diagrams role in F-UML is investigated in software performance modeling process. To get the aim, a fuzzy sub-profile is used.

Keywords: Fuzzy System, Software Development Model, Software Performance Evaluation, UML

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Authors: Dominykas Broga

Abstract:

Until recently it would have been unusual to consider classifying population movements and refugees as security problem. However, efforts at shaping our world to make ourselves secure have paradoxically led to ever greater insecurity. The feeling of uncertainty, pertinent throughout all discourses of security, has led to the creation of security production into seemingly benign routines of everyday life. Yet, the paper argues, neither of security discourses accounted for, disclosed and challenged the fundamental aporias embedded in Western security narratives. In turn, the paper aims to unpick the conventional security wisdom, which is haunted with strong ontologies, embedded in the politics of Orientalism, and (in)security nexus. The paper concludes that current security affair conceals the integral impossibility of fulfilling its very own promise of assured security. The paper also provides suggestions about alternative security discourse based on mutual dialogue.

Keywords: Identity, (in)security, migration, ontology

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Authors: A. Aydarous, M. El Ghazaly

Abstract:

The purpose of this study was to investigate the response of the newly released Gafchromic HD-V2 film for alpha particle of 5.5 MeV. Gafchromic HD-V2 was exposed to alpha particles of energy 5 MeV from 241Am for different durations. Then the films were scanned with a flatbed scanner. The dose response curve up to 2200 Gy has been achieved. The film’s reproducibility and sensitivity were evaluated. The results obtained show that the net optical density increases almost exponentially with the increase in the exposure time, and it becomes saturated after prolonged exposure times. The red channel shows the highest sensitivity, with a value of 4 x 10-3 Gy-1 at netOD of 0.4. The inter-film reproducibility was measured and the relative uncertainty found was 1.7 %, 2.1 % and 2.3 % for grey, red and green channels, respectively.

Keywords: Alpha dosimetry, 241Am, Gafchromic film.

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Authors: Musbah M. Aqel, P. K. Mahanti, Soumya Banerjee

Abstract:

This paper describes a simulation model for analyzing artificial emotion injected to design the game characters. Most of the game storyboard is interactive in nature and the virtual characters of the game are equipped with an individual personality and dynamic emotion value which is similar to real life emotion and behavior. The uncertainty in real expression, mood and behavior is also exhibited in game paradigm and this is focused in the present paper through a fuzzy logic based agent and storyboard. Subsequently, a pheromone distribution or labeling is presented mimicking the behavior of social insects.

Keywords: Artificial Emotion, Fuzzy logic, Game character, Pheromone label

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Authors: Bogdan Walek, Vladimir Bradac, Radim Farana

Abstract:

Distance learning systems offer useful methods of learning and usually contain a final course test or another form of test. The paper proposes a web application for evaluating tests using an expert system in distance learning systems. The proposed web application is appropriate for didactic tests or tests with results for subsequent studying follow-up courses. The web application works with test questions and uses an expert system and LFLC tool for test evaluation. After test evaluation, the results are visualized and shown to the student.

Keywords: Distance learning, test, uncertainty, fuzzy, expert system, student.

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Authors: M. Schulze, P. Crespo Del Granado

Abstract:

This paper considers the influence of promotion instruments for renewable energy sources (RES) on a multi-energy modeling framework. In Europe, so called Feed-in Tariffs are successfully used as incentive structures to increase the amount of energy produced by RES. Because of the stochastic nature of large scale integration of distributed generation, many problems have occurred regarding the quality and stability of supply. Hence, a macroscopic model was developed in order to optimize the power supply of the local energy infrastructure, which includes electricity, natural gas, fuel oil and district heating as energy carriers. Unique features of the model are the integration of RES and the adoption of Feed-in Tariffs into one optimization stage. Sensitivity studies are carried out to examine the system behavior under changing profits for the feed-in of RES. With a setup of three energy exchanging regions and a multi-period optimization, the impact of costs and profits are determined.

Keywords: Distributed generation, optimization methods, power system modeling, renewable energy.

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Authors: Yanhui Zhang, Wenyu Yang

Abstract:

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Keywords: Bayesian method, damage detection, fiber Bragg grating, structural health monitoring.

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Authors: Youguo Wang, Lenan Wu

Abstract:

We discuss the signal detection through nonlinear threshold systems. The detection performance is assessed by the probability of error Per . We establish that: (1) when the signal is complete suprathreshold, noise always degrades the signal detection both in the single threshold system and in the parallel array of threshold devices. (2) When the signal is a little subthreshold, noise degrades signal detection in the single threshold system. But in the parallel array, noise can improve signal detection, i.e., stochastic resonance (SR) exists in the array. (3) When the signal is predominant subthreshold, noise always can improve signal detection and SR always exists not only in the single threshold system but also in the parallel array. (4) Array can improve signal detection by raising the number of threshold devices. These results extend further the applicability of SR in signal detection.

Keywords: Probability of error, signal detection, stochasticresonance, threshold system.

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Authors: Ali Nadi, Ali Edrissi

Abstract:

Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: Disaster management, real-time demand, reinforcement learning, relief demand.

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Authors: M. Saravanan, J. Raja Murugadoss, V. Jayanthi

Abstract:

Optimal design of structure has a main role in reduction of material usage which leads to deduction in the final cost of construction projects. Evolutionary approaches are found to be more successful techniques for solving size and shape structural optimization problem since it uses a stochastic random search instead of a gradient search. By reviewing the recent literature works the problem found was the optimization of weight. A new meta-heuristic algorithm called as Cuckoo Search (CS) Algorithm has used for the optimization of the total weight of the truss structures. This paper has used set of 10 bars and 25 bars trusses for the testing purpose. The main objective of this work is to reduce the number of iterations, weight and the total time consumption. In order to demonstrate the effectiveness of the present method, minimum weight design of truss structures is performed and the results of the CS are compared with other algorithms.

Keywords: Cuckoo search algorithm, levy’s flight, meta-heuristic, optimal weight.

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Authors: M.H.Aziz, Erik L.J.Bohez, Manukid Parnichkun, Chanchal Saha

Abstract:

Petri Net (PN) has proven to be effective graphical, mathematical, simulation, and control tool for Discrete Event Systems (DES). But, with the growth in the complexity of modern industrial, and communication systems, PN found themselves inadequate to address the problems of uncertainty, and imprecision in data. This gave rise to amalgamation of Fuzzy logic with Petri nets and a new tool emerged with the name of Fuzzy Petri Nets (FPN). Although there had been a lot of research done on FPN and a number of their applications have been anticipated, but their basic types and structure are still ambiguous. Therefore, in this research, an effort is made to categorize FPN according to their structure and algorithms Further, literature review of the applications of FPN in the light of their classifications has been done.

Keywords: Discrete event systems, Fuzzy logic, Fuzzy Petri nets, and Petri nets.

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