Agency: European Commission | Branch: H2020 | Program: CSA | Phase: WATER-4a-2014 | Award Amount: 1.58M | Year: 2015
FREEWAT aims at promoting water management and planning by simplifying the application of the Water Framework Directive and other EU water related Directives. FREEWAT will be an open source and public domain GIS integrated modelling environment for the simulation of water quantity and quality in surface water and groundwater with an integrated water management and planning module. Specific objectives of the FREEWAT project are: - to coordinate previous EU and national funded research to integrate existing software modules for water management in a single environment into the GIS based FREEWAT; - to support the FREEWAT application in an innovative participatory approach gathering technical staff and relevant stakeholders (in primis policy and decision makers) in designing scenarios for the proper application of water policies. FREEWAT will initiate a process aimed at filling the gap between EU and US on widespread-standardised ICT tools and models for management of water quantity and quality and will set a well recognisable and flagship initiative. The open source characteristics of the platform allow to consider this an initiative ad includendum (looking for inclusion of other entities), as further research institutions, private developers etc. may contribute to the platform development. Through creating a common environment among water research/professionals, policy makers and implementers, FREEWAT main impact will be on enhancing science- and participatory approach and evidence-based decision making in water resource management, hence producing relevant and appropriate outcomes for policy implementation. The Consortium is constituted by partners from various water sectors from 11 EU countries, plus Switzerland, Turkey and Ukraine. Synergies with the UNESCO HOPE initiative on free and open source software in water management greatly boost the value of the project. Large stakeholders involvement guarantees results dissemination and exploitation.
Akay B.,Erciyes University |
Karaboga D.,Erciyes University
Information Sciences | Year: 2012
Swarm intelligence is a research field that models the collective intelligence in swarms of insects or animals. Many algorithms that simulates these models have been proposed in order to solve a wide range of problems. The Artificial Bee Colony algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behaviour of honey bee colonies. In this work, modified versions of the Artificial Bee Colony algorithm are introduced and applied for efficiently solving real-parameter optimization problems. © 2010 Elsevier Inc. All rights reserved.
Civicioglu P.,Erciyes University
Information Sciences | Year: 2013
In this paper, a new two-population based global search algorithm, the Artificial Cooperative Search Algorithm (ACS), is introduced. ACS algorithm has been developed to be used in solving real-valued numerical optimization problems. For purposes of examining the success of ACS algorithm in solving numerical optimization problems, 91 benchmark problems that have different specifications were used in the detailed tests. The success of ACS algorithm in solving the related benchmark problems was compared to the successes obtained by PSO, SADE, CLPSO, BBO, CMA-ES, CK and DSA algorithms in solving the related benchmark problems by using Wilcoxon Signed-Rank Statistical Test with Bonferroni-Holm correction. The results obtained in the statistical analysis demonstrate that the success achieved by ACS algorithm in solving numerical optimization problems is better in comparison to the other computational intelligence algorithms used in this paper. © 2012 Elsevier Inc. All rights reserved.
Civicioglu P.,Erciyes University
Computers and Geosciences | Year: 2012
In order to solve numerous practical navigational, geodetic and astro-geodetic problems, it is necessary to transform geocentric cartesian coordinates into geodetic coordinates or vice versa. It is very easy to solve the problem of transforming geodetic coordinates into geocentric cartesian coordinates. On the other hand, it is rather difficult to solve the problem of transforming geocentric cartesian coordinates into geodetic coordinates as it is very hard to define a mathematical relationship between the geodetic latitude (φ) and the geocentric cartesian coordinates (X, Y, Z). In this paper, a new algorithm, the Differential Search Algorithm (DS), is presented to solve the problem of transforming the geocentric cartesian coordinates into geodetic coordinates and its performance is compared with the performances of the classical methods (i.e., Borkowski, 1989; Bowring, 1976; Fukushima, 2006; Heikkinen, 1982; Jones, 2002; Zhang, 2005; Borkowski, 1987; Shu, 2010 and Lin, 1995) and Computational-Intelligence algorithms (i.e., ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES). The statistical tests realized for the comparison of performances indicate that the problem-solving success of DS algorithm in transforming the geocentric cartesian coordinates into geodetic coordinates is higher than those of all classical methods and Computational-Intelligence algorithms used in this paper. © 2011 Elsevier Ltd.
Akay B.,Erciyes University
Applied Soft Computing Journal | Year: 2013
Segmentation is a critical task in image processing. Bi-level segmentation involves dividing the whole image into partitions based on a threshold value, whereas multilevel segmentation involves multiple threshold values. A successful segmentation assigns proper threshold values to optimise a criterion such as entropy or between-class variance. High computational cost and inefficiency of an exhaustive search for the optimal thresholds leads to the use of global search heuristics to set the optimal thresholds. An emerging area in global heuristics is swarm-intelligence, which models the collective behaviour of the organisms. In this paper, two successful swarm-intelligence-based global optimisation algorithms, particle swarm optimisation (PSO) and artificial bee colony (ABC), have been employed to find the optimal multilevel thresholds. Kapur's entropy, one of the maximum entropy techniques, and between-class variance have been investigated as fitness functions. Experiments have been performed on test images using various numbers of thresholds. The results were assessed using statistical tools and suggest that Otsu's technique, PSO and ABC show equal performance when the number of thresholds is two, while the ABC algorithm performs better than PSO and Otsu's technique when the number of thresholds is greater than two. Experiments based on Kapur's entropy indicate that the ABC algorithm can be efficiently used in multilevel thresholding. Moreover, segmentation methods are required to have a minimum running time in addition to high performance. Therefore, the CPU times of ABC and PSO have been investigated to check their validity in real-time. The CPU time results show that the algorithms are scalable and that the running times of the algorithms seem to grow at a linear rate as the problem size increases. © 2012 Elsevier B.V. All rights reserved.
Cobaner M.,Erciyes University
Journal of Hydrology | Year: 2011
The potential of two different adaptive network-based fuzzy inference systems (ANFIS) based neuro-fuzzy systems in modeling of reference evapotranspiration (ET0) are investigated in this paper. The two neuro-fuzzy systems are: (1) grid partition based fuzzy inference system, named G-ANFIS, and (2) subtractive clustering based fuzzy inference system, named S-ANFIS. In the first part of the study, the performance of resultant FIS was compared and the effect of parameters was investigated. Various daily climatic data, that is, solar radiation, air temperature, relative humidity and wind speed from Santa Monica, in Los Angeles, USA, are used as inputs to the FIS models so as to estimate ET0 obtained using the FAO-56 Penman-Monteith equation. In the second part of the study, the estimates of the FIS models are compared with those of artificial neural network (ANN) approach, namely, multi-layer perceptron (MLP), and three empirical models, namely, CIMIS Penman, Hargreaves and Ritchie methods. Root mean square error, mean absolute error and determination coefficient statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it is found that the S-ANFIS model yields plausible accuracy with fewer amounts of computations as compared to the G-ANFIS and MLP models in modeling the ET0 process. © 2010 Elsevier B.V.
Aydogan E.K.,Erciyes University
Expert Systems with Applications | Year: 2011
In today's organizations, performance measurement comes more to the foreground with the advancement in the high technology. So as to manage this power, which is an important element of the organizations, it is needed to have a performance measurement system. Increased level of competition in the business environment and higher customer requirements forced industry to establish a new philosophy to measure its performance beyond the existing financial and non-financial based performance indicators. In this paper, a conceptual performance measurement framework that takes into account company-level factors is presented for a real world application problem. In order to use the conceptual framework for measuring performance, a methodology that takes into account both quantitative and qualitative factors and the interrelations between them should be utilized. For this reason, an integrated approach of analytic hierarchy process (AHP) improved by rough sets theory (Rough-AHP) and fuzzy TOPSIS method is proposed to obtain final ranking. © 2010 Elsevier Ltd. All rights reserved.
Tokalioglu S.,Erciyes University
Food Chemistry | Year: 2012
The concentrations of Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr and Pb elements in thirty medicinal herb samples widely consumed in Kayseri, Turkey were determined by using inductively coupled plasma mass spectrometry (ICP-MS). The samples were digested with concentrated nitric acid and hydrogen peroxide in a microwave system. The decreasing sequence of the mean metal levels in medicinal herbs is as follows: Fe > Sr > Mn > Zn > Rb > Cu > Ni > Cr > Co > Pb. Correlation analysis, principal component analysis and cluster analysis were applied to the data matrix to evaluate analytical results. It was found that four principal components account for 80.6% of the total variance in the data. In order to verify the accuracy of the method, GBW07605 Tea Certified Reference Material was analysed. © 2012 Elsevier Ltd. All rights reserved.
Erkaya S.,Erciyes University
Robotics and Computer-Integrated Manufacturing | Year: 2012
In this study, effects of joint clearance on a welding robot manipulator are investigated. Theoretical analysis is performed for different clearance sizes. By using the nonlinear spring-damper characteristic, contact model in revolute joint with clearance is established and the friction effect is performed using the Coulomb friction model. Then the simulation is carried out to investigate the kinematic and dynamic characteristics of the welding robot manipulator with joint clearance. For the case of two different clearance sizes, the results show that the joint clearance causes to degradation of kinematic and dynamic performance of the system. Even if the clearance size is small, it has a crucial role on amplitudes of the end-effectors accelerations and joint forces. © 2012 Elsevier Ltd.
Duran Toksar M.,Erciyes University
Computers and Operations Research | Year: 2011
We present a single-machine problem with the unequal release times under learning effect and deteriorating jobs when the objective is minimizing the makespan. In this study, we introduced a scheduling model with unequal release times in which both job deterioration and learning exist simultaneously. By the effects of learning and deterioration, we mean that the processing time of a job is defined by increasing function of its execution start time and position in the sequence. A branch-and-bound algorithm incorporating with several dominance properties and lower bounds is developed to derive the optimal solution. A heuristic algorithm is proposed to obtain a near-optimal solution. The computational experiments show that the branch-and-bound algorithm can solve instances up to 30 jobs, and the average error percentage of the proposed heuristic is less than 0.16%. © 2010 Elsevier Ltd. All rights reserved.