Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1328

Search results for: Demand Management

1328 Framework for Spare Inventory Management

Authors: Eman M. Wahba, Noha M. Galal, Khaled S. El-Kilany

Abstract:

Spare parts inventory management is one of the major areas of inventory research. Analysis of recent literature showed that an approach integrating spare parts classification, demand forecasting, and stock control policies is essential; however, adapting this integrated approach is limited. This work presents an integrated framework for spare part inventory management and an Excel based application developed for the implementation of the proposed framework. A multi-criteria analysis has been used for spare classification. Forecasting of spare parts- intermittent demand has been incorporated into the application using three different forecasting models; namely, normal distribution, exponential smoothing, and Croston method. The application is also capable of running with different inventory control policies. To illustrate the performance of the proposed framework and the developed application; the framework is applied to different items at a service organization. The results achieved are presented and possible areas for future work are highlighted.

Keywords: Demand forecasting, intermittent demand, inventory management, integrated approach, spare parts, spare part classification

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1327 A Reinforcement Learning Approach for Evaluation of Real-Time Disaster Relief Demand and Network Condition

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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1326 Elasticity Model for Easing Peak Hour Demand for Metrorail Transport System

Authors: P. K. Sarkar, Amit Kumar Jain

Abstract:

The demand for Urban transportation is characterised by a large scale temporal and spatial variations which causes heavy congestion inside metro trains in peak hours near Centre Business District (CBD) of the city. The conventional approach to address peak hour congestion, metro trains has been to increase the supply by way of introduction of more trains, increasing the length of the trains, optimising the time table to increase the capacity of the system. However, there is a limitation of supply side measures determined by the design capacity of the systems beyond which any addition in the capacity requires huge capital investments. The demand side interventions are essentially required to actually spread the demand across the time and space. In this study, an attempt has been made to identify the potential Transport Demand Management tools applicable to Urban Rail Transportation systems with a special focus on differential pricing. A conceptual price elasticity model has been developed to analyse the effect of various combinations of peak and nonpeak hoursfares on demands. The elasticity values for peak hour, nonpeak hour and cross elasticity have been assumed from the relevant literature available in the field. The conceptual price elasticity model so developed is based on assumptions which need to be validated with actual values of elasticities for different segments of passengers. Once validated, the model can be used to determine the peak and nonpeak hour fares with an objective to increase overall ridership, revenue, demand levelling and optimal utilisation of assets.

Keywords: Congestion, differential pricing, elasticity, transport demand management, urban transportation.

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1325 Demand Response from Residential Air Conditioning Load Using a Programmable Communication Thermostat

Authors: Saurabh Chanana, Monika Arora

Abstract:

Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand. 

Keywords: Demand response, Home energy management Programmable communicating thermostat, Thermostatically controlled appliances.

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1324 Water Demand Prediction for Touristic Mecca City in Saudi Arabia using Neural Networks

Authors: Abdel Hamid Ajbar, Emad Ali

Abstract:

Saudi Arabia is an arid country which depends on costly desalination plants to satisfy the growing residential water demand. Prediction of water demand is usually a challenging task because the forecast model should consider variations in economic progress, climate conditions and population growth. The task is further complicated knowing that Mecca city is visited regularly by large numbers during specific months in the year due to religious occasions. In this paper, a neural networks model is proposed to handle the prediction of the monthly and yearly water demand for Mecca city, Saudi Arabia. The proposed model will be developed based on historic records of water production and estimated visitors- distribution. The driving variables for the model include annuallyvarying variables such as household income, household density, and city population, and monthly-varying variables such as expected number of visitors each month and maximum monthly temperature.

Keywords: Water demand forecast; Neural Networks model; water resources management; Saudi Arabia.

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1323 Integrated Water Management for Lafarge Cement-Jordan

Authors: Azzam Hamaideh, Abbas Al-Omari, Michael Sturm

Abstract:

This study aims at implementing integrated water resources management principles to the Lafarge Cement Jordan at Al-Fuhais plant. This was accomplished by conducting water audits at all water consuming units in the plant. Based on the findings of the water audit, an action plan to improve water use efficiency in the plant was proposed. The main elements of which are installing water saving devices, re-use of the treated wastewater, water harvesting, raising the awareness of the employees, and linking the plant to the water demand management unit at the Ministry of Water and Irrigation.

The analysis showed that by implementing the proposed action plan, it is expected that the industrial water demand can be satisfied from non-conventional resources including treated wastewater and harvested water. As a consequence, fresh water can be used to increase the supply to Al-Fuhais city which is expected to reflect positively on the relationship between the factory and the city. 

Keywords: Integrated water resources management, non-conventional water resources, water awareness, water demand management, water harvesting, water saving devices.

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1322 Key Strategies for a Competitive Supply Chain

Authors: Ajay Verma, Nitin Seth

Abstract:

In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature and researchers have tried to identify variables of supply chain competitiveness. This paper highlights some of the concepts of supply chain competitiveness and tries to identify select variables on the basis of literature review. Further, the paper tries to highlight the importance of the identified variables in the achievement of supply chain competitiveness. The aim is to explore the concept and to motivate researchers to further investigate the unexplored areas of this important subject domain.

Keywords: Supply Chain Competitiveness, Demand Management, Integration, Inventory Management, Flexibility, Information Technology.

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1321 Demand and Supply Chain Simulation in Telecommunication Industry by Multi-Rate Expert Systems

Authors: Andrus Pedai, Igor Astrov

Abstract:

In modern telecommunications industry, demand & supply chain management (DSCM) needs reliable design and versatile tools to control the material flow. The objective for efficient DSCM is reducing inventory, lead times and related costs in order to assure reliable and on-time deliveries from manufacturing units towards customers. In this paper the multi-rate expert system based methodology for developing simulation tools that would enable optimal DSCM for multi region, high volume and high complexity manufacturing environment was proposed.

Keywords: Demand & supply chain management, expert systems, inventory control, multi-rate control, performance metrics.

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1320 Strategic Management of a Geoscience Education and Training Program

Authors: Lee Ock-Sun

Abstract:

The effective development of a geoscience education and training program takes account of the rapidly changing environment in the geoscience market, includes information about resource-rich countries which have international education demands. In this paper, we introduce the geoscience program run by the International School for Geoscience Resources at the Korea Institute of Geoscience and Mineral Resources (IS-Geo of KIGAM), and show its remarkable performance. To further effective geoscience program planning and operation, we present recommendations for strategic management for customer-oriented operation with a more favorable program format and advanced training aids. Above all, the IS-Geo of KIGAM should continue improve through ‘plan-do-see-feedback’ activities based on the recommendations.

Keywords: Demand survey, geoscience program, program performance, strategic management.

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1319 Physiological and Psychological Influence on Office Workers during Demand Response

Authors: Megumi Nishida, Naoya Motegi, Takurou Kikuchi, Tomoko Tokumura

Abstract:

In recent years, the power system has been changed and a flexible power pricing system such as demand response has been sought in Japan. The demand response system works simply in the household sector and the owner as the decision-maker, can benefit from power saving. On the other hand, the execution of demand response in the office building is more complex than in the household because various people such as owners, building administrators and occupants are involved in the decision-making process. While the owners benefit from demand saving, the occupants are exposed to restricted benefits of a demand-saved environment. One of the reasons is that building systems are usually under centralized management and each occupant cannot choose freely whether to participate in demand response or not. In addition, it is unclear whether incentives give occupants the motivation to participate. However, the recent development of IT and building systems enables the personalized control of the office environment where each occupant can control the lighting level or temperature individually. Therefore, it can be possible to have a system which each occupant can make a decision of whether or not to participate in demand response in the office building. This study investigates personal responses to demand response requests, under the condition where each occupant can adjust their brightness individually in their workspace. Once workers participate in the demand response, their desk-lights are automatically turned off. The participation rates in the demand response events are compared among four groups, which are divided by different motivation, the presence, or absence of incentives and the method of participation. The result shows that there are significant differences of participation rates in demand response event between four groups. The method of participation has a large effect on the participation rate. The “Opt-out” groups where the occupants are automatically enrolled in a demand response event if they do not express non-participation have the highest participation rate in the four groups. Incentives also have an effect on the participation rate. This study also reports on the impact of low illumination office environment on the occupants, such as stress or fatigue. The electrocardiogram and the questionnaire are used to investigate the autonomic nervous activity and subjective fatigue symptoms of the occupants. There is no big difference between dim workspace during demand response event and bright workspace in autonomic nervous activity and fatigue.

Keywords: Demand response, illumination, questionnaire, electrocardiograph.

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1318 Intelligent Caching in on-demand Routing Protocol for Mobile Adhoc Networks

Authors: Shobha.K.R., K. Rajanikanth

Abstract:

An on-demand routing protocol for wireless ad hoc networks is one that searches for and attempts to discover a route to some destination node only when a sending node originates a data packet addressed to that node. In order to avoid the need for such a route discovery to be performed before each data packet is sent, such routing protocols must cache routes previously discovered. This paper presents an analysis of the effect of intelligent caching in a non clustered network, using on-demand routing protocols in wireless ad hoc networks. The analysis carried out is based on the Dynamic Source Routing protocol (DSR), which operates entirely on-demand. DSR uses the cache in every node to save the paths that are learnt during route discovery procedure. In this implementation, caching these paths only at intermediate nodes and using the paths from these caches when required is tried. This technique helps in storing more number of routes that are learnt without erasing the entries in the cache, to store a new route that is learnt. The simulation results on DSR have shown that this technique drastically increases the available memory for caching the routes discovered without affecting the performance of the DSR routing protocol in any way, except for a small increase in end to end delay.

Keywords: Caching, DSR, on demand routing, MANET.

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1317 A DMB-TCA Simulation Method for On-Road Traffic Travel Demand Impact Analysis

Authors: Zundong Zhang, Limin Jia, Zhao Tian, Yanfang Yang

Abstract:

Travel Demands influence micro-level traffic behavior, furthermore traffic states. In order to evaluate the effect of travel demands on traffic states, this paper introduces the Demand- Motivation-Behaviors (DMB) micro traffic behavior analysis model which denotes that vehicles behaviors are determines by motivations that relies on traffic demands from the perspective of behavior science. For vehicles, there are two kinds of travel demands: reaching travel destinations from orientations and meeting expectations of travel speed. To satisfy travel demands, the micro traffic behaviors are delivered such as car following behavior, optional and mandatory lane changing behaviors. Especially, mandatory lane changing behaviors depending on travel demands take strong impact on traffic states. In this paper, we define the DMB-based cellular automate traffic simulation model to evaluate the effect of travel demands on traffic states under the different δ values that reflect the ratio of mandatory lane-change vehicles.

Keywords: Demand-Motivation-Behavior, Mandatory Lane Changing, Traffic Cellular Automata.

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1316 Outbound Tourism in Developed Countries: Analysis of the Trends, Behavior and the Transformation of the Moroccan Demand for International Travels

Authors: M. Boukhrouk, R. Ed-Dali

Abstract:

Outbound tourism in Morocco, as in the majority of developing countries, reveals some of the aspects of inequality between the north and the south. Considered by some researchers as one of the facets of the development crisis, access to tourism and especially international tourism is a chance for a small minority with financial means, while the vast portions of the population dream rather of immigrating to a developed country for the sake of improving their standard of living. The right to travel is also limited by visa requirements, procedures in host countries, security and technical measures and creates discrimination in the practice of tourism. These conditions do not seem to be favorable to the democratization of the practice of international tourism for the populations of the southern countries. This paper is a contribution to the reading of the trends of outbound tourism in developing countries through the example of Morocco. It highlights the different aspects of Moroccan outbound tourism, destinations and the behavior of tourists through an analysis of the offer of a sample of 50 travel agencies. In the same vein, it offers a reading grid of the possibilities offered for the development of outbound tourism and the various existing obstacles to the democratization of international outbound tourism in the southern countries. This reading reveals the transformation in the behavior of Moroccan international tourists as well as the profound changes in Moroccan society, through a model of statistical analysis.

Keywords: Demand, Hajj, Morocco, outbound tourism, tendency, Umrah.

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1315 Seismic Behavior and Capacity/Demand Analyses of a Simply-Supported Multi-Span Precast Bridge

Authors: Nasim Shatarat, Adel Assaf

Abstract:

This paper presents the results of an analytical study on the seismic response of a Multi-Span-Simply-Supported precast bridge in Washington State. The bridge was built in the early 1960's along Interstate 5 and was widened the first time in 1979 and the second time in 2001. The primary objective of this research project is to determine the seismic vulnerability of the bridge in order to develop the required retrofit measure. The seismic vulnerability of the bridge is evaluated using two seismic evaluation methods presented in the FHWA Seismic Retrofitting Manual for Highway Bridges, Method C and Method D2. The results of the seismic analyses demonstrate that Method C and Method D2 vary markedly in terms of the information they provide to the bridge designer regarding the vulnerability of the bridge columns.

Keywords: Bridges, Capacity, Demand, Seismic, Static pushover, Retrofit.

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1314 A Broadcasting Strategy for Interactive Video-on-Demand Services

Authors: Yu-Wei Chen, Li-Ren Han

Abstract:

In this paper, we employ the approach of linear programming to propose a new interactive broadcast method. In our method, a film S is divided into n equal parts and broadcast via k channels. The user simultaneously downloads these segments from k channels into the user-s set-top-box (STB) and plays them in order. Our method assumes that the initial p segments will not have fast-forwarding capabilities. Every time the user wants to initiate d times fast-forwarding, according to our broadcasting strategy, the necessary segments already saved in the user-s STB or are just download on time for playing. The proposed broadcasting strategy not only allows the user to pause and rewind, but also to fast-forward.

Keywords: Broadcasting, Near Video-on-Demand (VOD), Linear Programming, Video-Cassette-Recorder (VCR) Functions, Waiting Time.

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1313 A Study to Assess the Energy Saving Potential and Economic Analysis of an Agro Based Industry in Karnataka, India

Authors: Sangamesh G. Sakri, Akash N. Patil, Sadashivappa M. Kotli

Abstract:

Agro based industries in India are considered as the micro, small and medium enterprises (MSME). In India, MSMEs contribute approximately 8 percent of the country’s GDP, 42 percent of the manufacturing output and 40 percent of exports. The toor dal (scientific name Cajanus cajan, commonly known as yellow gram, pigeon pea) is the second largest pulse crop in India accounting for about 20% of total pulse production. The toor dal milling industry in India is one of the major agro-processing industries in the country. Most of the dal mills are concentrated in pulse producing areas, which are spread all over the country. In Karnataka state, Gulbarga is a district, where toor dal is the main crop and is grown extensively. There are more than 500 dal mills in and around the Gulbarga district to process dal. However, the majority of these dal milling units use traditional methods of processing which are energy and capital intensive. There exists a huge energy saving potential in these mills. An energy audit is conducted on a dal mill in Gulbarga to understand the energy consumption pattern to assess the energy saving potential, and an economic analysis is conducted to identify energy conservation opportunities.

Keywords: Conservation, demand side management, load curve, toor dal.

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1312 A Traffic Simulation Package Based on Travel Demand

Authors: Tuong Huan Nguyen, Quoc Bao Vo, Hai L. Vu

Abstract:

In this paper we propose a new traffic simulation package, TDMSim, which supports both macroscopic and microscopic simulation on free-flowing and regulated traffic systems. Both simulators are based on travel demands, which specify the numbers of vehicles departing from origins to arrive at different destinations. The microscopic simulator implements the carfollowing model given the pre-defined routes of the vehicles but also supports the rerouting of vehicles. We also propose a macroscopic simulator which is built in integration with the microscopic simulator to allow the simulation to be scaled for larger networks without sacrificing the precision achievable through the microscopic simulator. The macroscopic simulator also enables the reuse of previous simulation results when simulating traffic on the same networks at later time. Validations have been conducted to show the correctness of both simulators.

Keywords: Macroscopic, Microscopic, Simulation, Traffic, Travel demand, Fundamental diagrams.

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1311 Evidence of the Long-run Equilibrium between Money Demand Determinants in Croatia

Authors: B. Skrabic, N. Tomic-Plazibat

Abstract:

In this paper real money demand function is analyzed within multivariate time-series framework. Cointegration approach is used (Johansen procedure) assuming interdependence between money demand determinants, which are nonstationary variables. This will help us to understand the behavior of money demand in Croatia, revealing the significant influence between endogenous variables in vector autoregrression system (VAR), i.e. vector error correction model (VECM). Exogeneity of the explanatory variables is tested. Long-run money demand function is estimated indicating slow speed of adjustment of removing the disequilibrium. Empirical results provide the evidence that real industrial production and exchange rate explains the most variations of money demand in the long-run, while interest rate is significant only in short-run.

Keywords: Cointegration, Long-run equilibrium, Money demand function, Vector error correction model.

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1310 Optimal Production and Maintenance Policy for a Partially Observable Production System with Stochastic Demand

Authors: Leila Jafari, Viliam Makis

Abstract:

In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: Condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand.

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1309 Case Study of Bus Tourist-s Sightseeing Time in a New Sightseeing Spot

Authors: Takayuki Nanashima, Yoshiyuki Higuchi, Masao Ohta, Takashi Kuroda

Abstract:

As a result of traffic congestion caused by sightseeing and shuttle buses using park-and-ride parking lot near sightseeing spot, the waiting time for tourist increases. In this paper, when bus parking lot near sightseeing spot are overcrowded and full, a model for tourists getting off a bus on a congested road and transfer to the sightseeing spot by foot is proposed and verified. A model of getting off a bus on a congested road when the sightseeing parking lot is overcrowded was considered by the case analysis. As a result, effectiveness of the model of getting off a bus on a congested road could be quantitatively verified for times when parking capacity is exceeded and the bus parking lot next to the sightseeing spot is overcrowded.

Keywords: Transportation demand management, Park-and-ride, Traffic congestion, Tourist satisfaction.

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1308 Comparative Analysis of Ranunculus muricatus and Typha latifolia as Wetland Plants Applied for Domestic Wastewater Treatment in a Mesocosm Scale Study

Authors: S. Aziz, M. Ali, S. Asghar, S. Ahmed

Abstract:

Comparing other methods of waste water treatment, constructed wetlands are one of the most fascinating practices because being a natural process they are eco-friendly have low construction and maintenance cost and have considerable capability of wastewater treatment. The current research was focused mainly on comparison of Ranunculus muricatus and Typha latifolia as wetland plants for domestic wastewater treatment by designing and constructing efficient pilot scale horizontal subsurface flow mesocosms. Parameters like chemical oxygen demand, biological oxygen demand, phosphates, sulphates, nitrites, nitrates, and pathogenic indicator microbes were studied continuously with successive treatments. Treatment efficiency of the system increases with passage of time and with increase in temperature. Efficiency of T. latifolia planted setups in open environment was fairly good for parameters like COD and BOD5 which was showing reduction up to 82.5% for COD and 82.6% for BOD5 while DO was increased up to 125%. Efficiency of R. muricatus vegetated setup was also good but lowers than that of T. latifolia planted showing 80.95% removal of COD and BOD5. Ranunculus muricatus was found effective in reducing bacterial count in wastewater. Both macrophytes were found promising in wastewater treatment.

Keywords: Biological oxygen demand, chemical oxygen demand, horizontal subsurface flow, Total suspended solids, Wetland.

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1307 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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1306 Feasibility Studies through Quantitative Methods: The Revamping of a Tourist Railway Line in Italy

Authors: Armando Cartenì, Ilaria Henke

Abstract:

Recently, the Italian government has approved a new law for public contracts and has been laying the groundwork for restarting a planning phase. The government has adopted the indications given by the European Commission regarding the estimation of the external costs within the Cost-Benefit Analysis, and has been approved the ‘Guidelines for assessment of Investment Projects’. In compliance with the new Italian law, the aim of this research was to perform a feasibility study applying quantitative methods regarding the revamping of an Italian tourist railway line. A Cost-Benefit Analysis was performed starting from the quantification of the passengers’ demand potentially interested in using the revamped rail services. The benefits due to the external costs reduction were also estimated (quantified) in terms of variations (with respect to the not project scenario): climate change, air pollution, noises, congestion, and accidents. Estimations results have been proposed in terms of the Measure of Effectiveness underlying a positive Net Present Value equal to about 27 million of Euros, an Internal Rate of Return much greater the discount rate, a benefit/cost ratio equal to 2 and a PayBack Period of 15 years.

Keywords: Cost-benefit analysis, evaluation analysis, demand management, external cost, transport planning, quality.

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1305 Uniform Distribution of Ductility Demand in Irregular Bridges using Shape Memory Alloy

Authors: Seyed Mohyeddin Ghodratian, Mehdi Ghassemieh, Mohammad Khanmohammadi

Abstract:

Excessive ductility demand on shorter piers is a common problem for irregular bridges subjected to strong ground motion. Various techniques have been developed to reduce the likelihood of collapse of bridge due to failure of shorter piers. This paper presents the new approach to improve the seismic behavior of such bridges using Nitinol shape memory alloys (SMAs). Superelastic SMAs have the ability to remain elastic under very large deformation due to martensitic transformation. This unique property leads to enhanced performance of controlled bridge compared with the performance of the reference bridge. To evaluate the effectiveness of the devices, nonlinear time history analysis is performed on a RC single column bent highway bridge using a suite of representative ground motions. The results show that this method is very effective in limiting the ductility demand of shorter pier.

Keywords: bridge, ductility demand, irregularity, shape memory alloy

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1304 Comparison of ANFIS and ANN for Estimation of Biochemical Oxygen Demand Parameter in Surface Water

Authors: S. Areerachakul

Abstract:

Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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1303 Forecasting Models for Steel Demand Uncertainty Using Bayesian Methods

Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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1302 Investigating the Effective Parameters in Determining the Type of Traffic Congestion Pricing Schemes in Urban Streets

Authors: Saeed Sayyad Hagh Shomar

Abstract:

Traffic congestion pricing – as a strategy in travel demand management in urban areas to reduce traffic congestion, air pollution and noise pollution – has drawn many attentions towards itself. Unlike the satisfying findings in this method, there are still problems in determining the best functional congestion pricing scheme with regard to the situation. The so-called problems in this process will result in further complications and even the scheme failure. That is why having proper knowledge of the significance of congestion pricing schemes and the effective factors in choosing them can lead to the success of this strategy. In this study, first, a variety of traffic congestion pricing schemes and their components are introduced; then, their functional usage is discussed. Next, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of pricing schemes are described. The results, accordingly, show that the selection of the best scheme depends on various parameters. Finally, based on examining the effective parameters, it is concluded that the implementation of area-based schemes (cordon and zonal) has been more successful in non-diversion of traffic. That is considering the topology of the cities and the fact that traffic congestion is often created in the city centers, area-based schemes would be notably functional and appropriate.

Keywords: Congestion pricing, demand management, flat toll, variable toll.

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1301 Investigating the Demand for Short-shelf Life Food Products for SME Wholesalers

Authors: Yamini Raju, Parminder S. Kang, Adam Moroz, Ross Clement, Ashley Hopwell, Alistair Duffy

Abstract:

Accurate forecasting of fresh produce demand is one the challenges faced by Small Medium Enterprise (SME) wholesalers. This paper is an attempt to understand the cause for the high level of variability such as weather, holidays etc., in demand of SME wholesalers. Therefore, understanding the significance of unidentified factors may improve the forecasting accuracy. This paper presents the current literature on the factors used to predict demand and the existing forecasting techniques of short shelf life products. It then investigates a variety of internal and external possible factors, some of which is not used by other researchers in the demand prediction process. The results presented in this paper are further analysed using a number of techniques to minimize noise in the data. For the analysis past sales data (January 2009 to May 2014) from a UK based SME wholesaler is used and the results presented are limited to product ‘Milk’ focused on café’s in derby. The correlation analysis is done to check the dependencies of variability factor on the actual demand. Further PCA analysis is done to understand the significance of factors identified using correlation. The PCA results suggest that the cloud cover, weather summary and temperature are the most significant factors that can be used in forecasting the demand. The correlation of the above three factors increased relative to monthly and becomes more stable compared to the weekly and daily demand.

Keywords: Demand Forecasting, Deteriorating Products, Food Wholesalers, Principal Component Analysis and Variability Factors.

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1300 Changing the Way South Africa Think about Parking Provision at Tertiary Institutions

Authors: M. C. Venter, G. Hitge, S. C. Krygsman, J. Thiart

Abstract:

For decades, South Africa has been planning transportation systems from a supply, rather than a demand side, perspective. In terms of parking, this relates to requiring the minimum parking provision that is enforced by city officials. Newer insight is starting to indicate that South Africa needs to re-think this philosophy in light of a new policy environment that desires a different outcome. Urban policies have shifted from reliance on the private car for access, to employing a wide range of alternative modes. Car dominated travel is influenced by various parameters, of which the availability and location of parking plays a significant role. The question is therefore, what is the right strategy to achieve the desired transport outcomes for SA. The focus of this paper is used to assess this issue with regard to parking provision, and specifically at a tertiary institution. A parking audit was conducted at the Stellenbosch campus of Stellenbosch University, monitoring occupancy at all 60 parking areas, every hour during business hours over a five-day period. The data from this survey was compared with the prescribed number of parking bays according to the Stellenbosch Municipality zoning scheme (requiring a minimum of 0.4 bays per student). The analysis shows that by providing 0.09 bays per student, the maximum total daily occupation of all the parking areas did not exceed an 80% occupation rate. It is concluded that the prevailing parking standards are not supportive of the new urban and transport policy environment, but that it is extremely conservative from a practical demand point of view.

Keywords: Parking provision, parking requirements, travel behaviour, travel demand management.

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1299 Wireless Distributed Load-Shedding Management System for Non-Emergency Cases

Authors: Taha Landolsi, A. R. Al-Ali, Tarik Ozkul, Mohammad A. Al-Rousan

Abstract:

In this paper, we present a cost-effective wireless distributed load shedding system for non-emergency scenarios. In power transformer locations where SCADA system cannot be used, the proposed solution provides a reasonable alternative that combines the use of microcontrollers and existing GSM infrastructure to send early warning SMS messages to users advising them to proactively reduce their power consumption before system capacity is reached and systematic power shutdown takes place. A novel communication protocol and message set have been devised to handle the messaging between the transformer sites, where the microcontrollers are located and where the measurements take place, and the central processing site where the database server is hosted. Moreover, the system sends warning messages to the endusers mobile devices that are used as communication terminals. The system has been implemented and tested via different experimental results.

Keywords: Smart Grid, Load shedding, Demand SideManagement, GSM Wireless Networks, SCADA systems.

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