Forecasting the energy demand of Turkey with a NN based on an improved Particle Swarm Optimization

WOS: 000417319700044Forecasting the future energy demand accurately is a critical issue, especially for countries like Turkey where the energy dependency ratio is high. This paper presents a neural network based on the particle swarm optimization algorithm with mutation (PSOM-NN) to enhance the prediction accuracy of the energy demand of Turkey. Unlike some studies in the field which are using all the observed data for training purpose, the proposed network used only a part of these data for training. Approximately 63 % and 37 % of the mentioned data are used for the training and test, respectively. Detrending is applied to the data to avoid nonlinear transfer functions that constrain the model to the input range values. The analysis of the results revealed that PSOM-NN produced better forecasts of energy demand compared to the earlier studies in terms of root-meansquare error, mean absolute percentage error and mean absolute deviation. Finally, future projections under different scenarios are also employed and discussed. It is believed that the proposed model could be applied to any country that needs accurate forecasts of the energy demand for sustainable energy policies

Determination of optimal cutting conditions in finish turning of austempered ductile iron using Taguchi design method

278-283This study presents optimization of process parameters using Taguchi design method in finish turning of austempered ductile iron. An orthogonal array of L18 was used; ANOVA was performed to identify significant factors affecting surface roughness (Ra) and primary cutting force (Fc). Optimum processes parameter combination was acquired by using analysis of signal-to-noise (S/N) ratio. For Ra and Fc values, prediction error was found to be within the confidence limit at 95% confidence level

Designing Public Policies to Support SME Innovation Capacity: Proposal of an Approach based on Innovativeness Profiles

WOS: 000410798000013It is crucial for enterprises to follow sustainable and competitive growth strategies to survive in the global market. Companies which cannot produce adequate levels of innovation outputs are likely to lose their competitiveness. Small and medium size enterprises (SMEs) which constitute a large part of enterprises face more diverse set of obstacles than larger enterprises. Thus, in many countries public policies that encourage innovation are encountered. In this study, an approach is proposed to design public policies based on innovation profiles of SMEs. The approach would lead to different strategic roadmaps and public support tools designed for SMEs with different innovative profiles. That would increase the contribution of SMEs to the country's overall technological development process and international competitiveness

Column Generation based solution for Bi-objective Gate Assignment Problems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In this paper, we present a column generation-based algorithm for the bi-objective gate assignment problem (GAP) to generate gate schedules that minimize squared slack time at the gates while satisfying passenger expectations by minimizing their walking distance. While most of the literature focuses on heuristic or metaheuristic solutions for the bi-objective GAP, we propose flow-based and column-based models that lead to exact or near optimal solution approaches. The developed algorithm calculates a set of solutions to approximate the Pareto front. The algorithm is applied to the over-constrained GAP where gates are a limited resource and it is not possible to serve every flight using a gate. Our test cases are based on real data from an international airport and include various instances with flight-to-gate ratios between 23.9 and 34.7. Numerical results reveal that a set of solutions representing a compromise between the passenger-oriented and robustness-oriented objectives may be obtained with a tight optimality gap and within reasonable computational time even for these difficult problems

Properties of Ni/Nano-TiO2 Composite Coatings Prepared by Direct and Pulse Current Electroplating

Pure nickel and nickel matrix composite coatings containing nano-TiO2 particles were produced under both direct and pulse current conditions from an additive-free nickel Watts' type bath. The surface morphology, crystal size, crystallographic orientation, and microhardness of nickel matrix and the amount of embedded nano-TiO2 particles in the composite coatings were investigated. The corrosion performance of the coatings was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy methods. The TiO2 particles embedded in the nickel matrix exerted strong influence on the texture of the growing nickel layer, changing its texture under both direct and pulse current conditions. The textural perfection of the deposits revealed that the presence of TiO2 particles led to the deteriorating of [100] preferred orientation. Under direct current conditions, the composite coating exhibited clearly [211] fiber orientation, while pulse current working exhibited a mixed crystal orientation through [100] and [211] axes. It is concluded that in the presence of TiO2 nanoparticles, the adsorption-desorption phenomena occurring on the metal surface are altered. The experimental results show that composite electrodeposits prepared under pulse plating conditions exhibited higher incorporation percentages than those obtained under direct plating conditions, at particularly 10 Hz and low duty cycles. The results revealed that pulse-plated Ni/TiO2 nanocomposite coating provided excellent anti-corrosion performance and presented higher microhardness

An Intrusion Detection System Based on a Hybrid Tabu-Genetic Algorithm

2017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEYWOS: 000426856900041In this paper, we proposed a framework for detecting network's intrusions using Genetic Algorithm (GA) with multiple criteria. First of all, we build an intrusion detection system (IDS) using a pure GA with multiple selection methods. Then, we proposed one of the few hybrid algorithms in the literature, which is hybridized using a GA and a Tabu search (TS) algorithm. The proposed hybrid algorithm and the pure GA were tested to detect malicious traffic using DARPA dataset. The test results revealed that the proposed hybrid algorithm gives a higher Detection Rate (DR) and Detection Accuracy (AC) compared to the pure GA.IEEE Adv Technol Human, Istanbul Teknik Univ, Gazi Univ, Atilim Univ, TBV, Akdeniz Univ, Tmmob Bilgisayar Muhendisleri Odas

A review on airport gate assignment problems: Single versus multi objective approaches

WOS: 000510947600002Assigning aircraft to gates is an important decision problem that airport professionals face every day. The solution of this problem has raised a significant research effort and many variants of this problem have been studied. In this paper, we review past work with a focus on identifying types of formulations, classifying objectives, and categorising solution methods. The review indicates that there is no standard formulation, that passenger oriented objectives are most common, and that more recent work are multi-objective. In terms of solution methods, heuristic and metaheuristic approaches are dominant which provides an opportunity to develop exact and approximate approaches both for the single and multi-objective problems. (C) 2019 Elsevier Ltd. All rights reserved.Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [(1059B191700275) 2219]The first author is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) (Grant No: 1059B191700275) 2219 Post Doctoral Research Fellowship Program during her research at WAnOpt Lab, University of Waterloo

Control Engineering and Robotics since Primary School: an Infrastructure for creating the Digital Twin model of the Learning Class

Control engineering has a cross-boundary nature because its applications span over a wide range of fields, among which science, technology, engineering, and mathematics (STEM). Creating an automation literacy from the Primary School's age is beneficial for pupils because it supports the development of valuable skills that allow the comprehension and analysis of real-world phenomena. Even if many researchers and policymakers have advocated for engineering education since early education, it is usually kept for undergraduate and graduate-level education. What prevents systems theory and control education from being integrated into K12 education is the lack of available educational resources and the lack of indicators to represent the learning gain of students. To help teachers in the latter aspect, a solution can be studying the entire process as a cyber-physical human system (CPHS). The paper consists of a brief report about the work carried out by authors to represent the entire classroom as a CPHS where the physical robots designed by students, humans (teachers and learners), and cybertechnologies are interconnected to accomplish a goal which is learning. The entire infrastructure could be seamlessly deployed into the classroom, supporting learning assessment and the feedback process starting from the deployment of a (quasi) real-time intelligent collection system

An exploration of the literature on the use of 'swarm intelligence-based techniques' for public service problems

The importance of studying public service systems and finding robust solutions to the problems encountered in public service management has increased considerably over the past decade. One of the main objectives is to find acceptable solutions to Public Service Problems (PSPs) within an affordable period of time. However, many PSPs remain difficult to solve within a reasonable time due to their complexity and dynamic nature. This requires solving PSPs with techniques which provide efficient algorithmic solutions. There has been increasing attention in the literature to solving PSPs through the use of Swarm Intelligence-Based Techniques (SIBTs) like ant colony optimisation, particle swarm optimisation, Bee(s) Algorithm (BA), etc. This paper presents a review of Swarm Intelligence (SI) applications in public services (including PSPs in specific application areas), as well as the models and SI algorithms that have been reported in the literature. [Received 30 January 2008; Revised 4 December 2008; Revised 17 March 2009; Accepted 23 March 2009]swarm intelligence; public services; ant colony optimisation; ACO; particle swarm optimisation; PSO; bees algorithm; public service management.