Erma Suryani

Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework

This paper deals with how to develop a model to forecast air passenger demand and to evaluate some policy scenarios related with runway and passenger terminal capacity expansion to meet the future demand. System dynamics frameworks can be used to model, to analyze and to generate scenario to increase the system performance because of its capability of representing physical and information flows, based on information feedback control that are continuously converted into decisions and actions. We found that airfare impact, level of service impact, GDP, population, number of flights per day and dwell time play an important roles in determining the air passenger volume, runway utilization and total additional area needed for passenger terminal capacity expansion.

Demand scenario analysis and planned capacity expansion: A system dynamics framework

This paper establishes an approach to develop models for forecasting demand and evaluating policy scenarios related to planned capacity expansion for meeting optimistic and pessimistic future demand projections. A system dynamics framework is used to model and to generate scenarios because of their capability of representing physical and information flows, which will enable us to understand the nonlinear dynamics behavior in uncertain conditions. These models can provide important inputs such as construction growth, GDP growth, and investment growth to specific business decisions such as planned capacity expansion policies that will improve the system performance.

DYNAMIC SIMULATION MODEL OF AIR CARGO DEMAND FORECAST AND TERMINAL CAPACITY PLANNING

This paper establishes an approach to forecast air cargo demand related to terminal capacity expansion. To balance capacity and demand, it is required to forecast the future demand based on optimistic and pessimistic projections to decide when and how much, the airport should expand the capacity. System dynamics simulation model can provide reliable forecast and generate scenarios to test alternative assumptions and decisions. It was found that GDP and FDI play an important role in fostering the demand. Terminal expansion would be required in 2018 based on the optimistic projection; meanwhile, based on pessimistic projection, the capacity can meet demand in 2030, which means no need to increase the capacity.

Automatic Clustering Combining Differential Evolution Algorithm and k -Means Algorithm

One of the most challenging problems in data clustering is to determine the number of clusters. This study intends to propose an improved differential evolution algorithm which integrates automatic clustering based differential evolution (ACDE) algorithm and k-means (ACDE-k-means) algorithm. It requires no prior knowledge about number of clusters. k-means algorithm is employed to tune cluster centroids in order to improve the performance of DE algorithm. To validate the performance of the proposed algorithm, two well-known data sets, Iris and Wine, are employed. The computational results indicate that the proposed ACDE-k-means algorithm is superior to classical DE algorithm.

Dynamics simulation model of demand and supply electricity energy public facilities and social sector case study East Java

Electrical energy is one important factor in the development of every nation, including Indonesia. Electrical energy has an important role in the development of both the economic and social aspects. Remember so large and important energy benefits of electricity while the power generation energy sources, especially those from non renewable resource limited presence, and to ensure the sustainability of energy sources is necessary pursued strategic steps to support the provision of electrical energy in an optimal and affordable. This paper explores how dynamic modeling can help generate future scenarios of electricity consumption. This modeling study the structure of complex systems and to test different scenarios. This paper have 3 Scenario such as, normal condition, optimistic condition(growth increase 0.5% per month), and pessimist condition(growth decrease 0.5% per month). Also a large number of variables, which affect the behavior could be considered. Power producers, suppliers and distributors requires knowledge of the total consumption to support their business, such as investment decisions of new substations. Modeling and simulation of the results obtained to analyze the electrical energy demand Social and Public sector based on current conditions and forecast electricity demand in the field of Social and Public in the future and how the availability of electricity in the future.

Dynamics simulation of air passenger forecasting and passenger terminal capacity expansion scenario in Yogyakarta Airport

Adisutjipto International Airport Yogyakarta has reached four times more than capacity allowed in 2015. The building capacity only accommodate 1,5 million passengers per year, but in 2015 there were 6 million passengers. For this reason, in 2016 the airport developing new airport, Kulon Progo Airport. Actually, since 2003, passenger terminal capacity already exceeded two times capacity allowed. To solve this problem, this research proposed new modeling-simulation-dynamic-system, that combine between GDP, population, terminal capacity and regulation from minister of transport to forecast passenger demand and time to expansion the airport. Simulation model utilized historical data in 2005–2015 to generate forecasting for 2016–2050. There were three scenarios used as consideration in determining policy, such as pessimistic, most likely, and optimistic scenario. In the pessimistic scenario models, the ideal for development is before 2031. In the most likely scenario models, the ideal time for development is before 2025. While the model of the optimistic scenario, the ideal time for development is before 2024.

A Simulation Model for Strategic Planning in Asset Management of Electricity Distribution Network

Asset management of electricity distribution network is required in order to improve the network reliability so as to reduce electricity energy distribution losses. Due to strategic asset management requires long-term predictions; it would require a simulation model. Simulation of asset management is an approach to predict the consequences of long-term financing on maintenance and renewal strategies in electrical energy distribution networks. In this research, the simulation method used is System Dynamics based on consideration that this method enables us to consider internal and external influenced factors. To obtain the model parameter, we utilized PLN Pamekasan for the case study. The results showed the reduction of low voltage network assets condition on average in the range 6% per year, the average decline in the transformer condition is approximately 6.6% per year, and the average decline in the condition of medium voltage network assets is approximately 4.4% per year. In general, the average technical losses average of 1,359,981.60 KWH / month or about 16,319,779.24 KWH / year.

Applying a Hybrid Data Mining Approach to Develop Carotid Artery Prediction Models

This paper performs a hybrid method for imbalanced medical data set with many features on it. A synthetic minority over-sampling technique (SMOTE) is used to solve two-class imbalanced problems. This method enhanced the significance of the small and specific region belonging to the positive class in the decision region. The SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Another method that used is Genetic Algorithm for feature selection. The proposed of this method is to receive the reduced redundancy of information among the selected features. On the other hand, this method emphasizes on selecting a subset of salient features with reduced number using a subset size determination scheme. Towards the end, selected features would be processed using back Propagation Network (NN) and Decision Tree to predict the accuracy of Carotid Artery Disease. Experimental results show that these methods achieved a high accuracy, so it can assist the doctors to provide some possibilities information to the patient.

Corrigendum: Corrigendum to Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework [Expert Systems with Applications 37 (3) (2010) 2324-2339]

The author regrets that the below citation was erroneous in the article, please find below the corrected one also. Citation which needs to be corrected is: ‘‘Poore, J.W., 1993. Forecasting the demand for air transportation services. Journal of Transportation Engineering, Virginia 19 (5), 22–34”. The correct one should be as follows, with a much longer title which was also mistakenly truncated: ‘‘Poore, J. W. (1992). Forecasting the demand for air transportation services: An analysis of the forecasts published by the International Civil Aviation Organization, Boeing, McDonnell Douglas, and Airbus Industries, Ph.D., Golden Gate University”.