Flower pollination algorithm approach for the transportation energy demand estimation in Turkey: model development and application

Korkmaz, Ersin; Akgüngör, Ali Payıdar

doi:10.1080/15567249.2019.1572835

Cited by 15 publications

(6 citation statements)

References 27 publications

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“…Both economic performance and the number of diesel vehicles should therefore increase diesel consumption. These coefficients are positive and statistically significant, and these findings are parallel with those of Korkmaz and Akgüngör (2018) and Sen and Uzunoz (2017).…”

Section: Methodology and Empirical Evidencesupporting

confidence: 54%

A measure of the informal sector for the Turkish diesel market

Yaz

Dogan

Berument

2021

Energy Sources, Part B: Economics, Planning, and Policy

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Measuring the size of the informal diesel market is important for determining tax revenue losses and identifying inefficiencies in tax policies. The conventional ways of assessing the informal sector entail either not allowing the measurement of the size of the informal sector across time or assuming a stable relationship between diesel consumption and a set of economic variables. This study assesses the informal sector of the Turkish diesel market by using the Kalman filter method. This method allows unobserved values to be estimated with observed variables. Using monthly interpolated GDP, official diesel consumption, and the number of diesel motor vehicles, Turkey's unobserved informal diesel fuel consumption between January 2005 and February 2020 is estimated. The results obtained with this estimation method reveal that the level of informal diesel consumption increased until 2012-2014; it then started to decline at the end of 2014 and started to increase again after 2018. These dates are associated with periods of economic recession, political developments, and the passing of antismuggling legislation.

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Section: Methodology and Empirical Evidencesupporting

confidence: 54%

A measure of the informal sector for the Turkish diesel market

Yaz

Dogan

Berument

2021

Energy Sources, Part B: Economics, Planning, and Policy

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“…When compared with the SS, BA, and FCFS, they showed that the proposed algorithm yields optimum results up to 100 planes and has the capacity to achieve good results in a short time up to 500 planes. Korkmaz and Akgüngör 13 applied the FPA approach to the energy demand forecast and achieved successful results. They reported that the algorithm makes predictions with lower percentage errors when compared to other approaches in the literature.…”

Section: Methodsmentioning

confidence: 99%

“…Expressions of global and local search, which are two important steps of the algorithm, are given in Equations ( 12) and (13).…”

Section: Butterfly Optimization Algorithmmentioning

confidence: 99%

“…Popular algorithms such as ABC, FPA, CSA, KH, Particle Swarm Optimization (PSO), Genetic Algorithm (GA) have been widely applied in many different studies 11 . These algorithms have been successfully applied in many different engineering problems such as energy, traffic, clustering 12‐14 . In the literature, there are many studies on air passenger and freight transport estimation models developed based on different techniques, the methods of determining the relationship between supply and demand, and the effect of socioeconomic variables and air transport variables on demand.…”

Section: Literature Reviewmentioning

confidence: 99%

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The forecasting of air transport passenger demands in Turkey by using novel meta‐heuristic algorithms

Korkmaz

Akgüngör

2021

Concurrency and Computation

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The imbalance between modes of transport in our country appears as the most important problem. Therefore, in air transportation, which has a significant increasing trend, estimating the passenger demand with directly related parameters and novel algorithms is important for Turkey. In this study, different prediction models were developed applying for the first time with five different meta-heuristic algorithms which are Flower Pollination Algorithm (FPA), Artificial Bee Colony Algorithm (ABC), Crow Search Algorithm (CSA), Krill Herd Algorithm (KH), and the Butterfly Optimization Algorithm (BOA) to estimate Turkey's air transport demand. While developing the models, Fuel Price, Gross Domestic Product per Capita, Seat Capacity, and Annual Fuel Consumption were selected as the model parameters. Although each model developed using different approaches is applicable, quadratic and power models developed using CSA showed the highest performance. For this reason, future projections were based on these models. Air transport passenger demand was examined using two scenarios in a process until 2035. In the first scenario, according to model forms, Turkey's future air transport passenger demand will reach about 460 and 490 million passengers, respectively. In the second scenario, the number of passengers will reach approximately 375 and 660 million for quadratic and power models, respectively. The results of this study will contribute to the evaluation of the current investment plans and the development of strategic plans that will meet the demands. Additionally, they will help take necessary measures and introduce some necessary regulations to ensure the income and expense balance so that the efficiency of airline companies can be improved. K E Y W O R D Sair transport passenger demand, artificial bee colony algorithm, butterfly optimization algorithm, crow search algorithm, flower pollination algorithm, krill herd algorithm INTRODUCTIONAir transport is one of the most preferred modes of transport by passengers in the world and in Turkey because it provides important benefits such as safety, speed, and comfort. Air transport, which has a very important place in terms of trade and tourism development, also contributes to the social development and economic growth of countries.Air transport has shown a rapid development worldwide after the Second World War. The most important reasons for this progress are the development of aircraft production technology in the war years, the desire of the pilots to transform their skills to a commercial profit, and the desire of countries to undertake development ventures by rapidly erasing the negative traces of the war. For all these reasons, passenger and freight

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“…The transport sector in Turkey, which is among developing countries and has a population of more than 80 million, constitutes about 20 -25% of total energy consumption. It is anticipated that this value will increase over time, according to the studies [6]. Moreover, this sector, which is responsible for 24% of CO 2 emission in 2017, is considered as one of the most important causes of environmental pollution [7].…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency in Rail Systems with Coasting Control Method Using GA and ABC Optimizations

2021

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Today, reducing the energy consumption of rail systems is one of the issues that attract researchers' attention. There are many methods to reduce energy consumption and coasting control method has been used in this study. The driving modelling of the vehicle has been carried out by considering all parameters. A new objective function has been determined and for optimization, genetic algorithm (GA) and artificial bee colony (ABC) algorithm have been preferred. The study has been tested with the data of Ankaray metro line. When the proposed optimized driving has been compared with practical driving of the vehicle, the energy savings rate is 13.79% in GA and 13.45% in ABC for a driving. Despite these significant savings ratios, the increase in travel time has been calculated at 1.7% in GA and 1.55% in ABC. When the obtained savings rates are considered annually, this study may greatly contribute to sustainable life.

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Flower pollination algorithm approach for the transportation energy demand estimation in Turkey: model development and application

Cited by 15 publications

References 27 publications

A measure of the informal sector for the Turkish diesel market

A measure of the informal sector for the Turkish diesel market

The forecasting of air transport passenger demands in Turkey by using novel meta‐heuristic algorithms

Energy Efficiency in Rail Systems with Coasting Control Method Using GA and ABC Optimizations

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