Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Gul, Muhammet(86)
- Güler, Ömer(69)
- Akkurt, Nevzat(68)
- Baskonus, Haci Mehmet(53)
- Tekin, H.O.(52)
- Bulut, Hasan(50)
- ALMisned, Ghada(49)
- Serdar, Osman(43)
- Yucesan, Melih(43)
- Paksoy, Mehmet Yavuz(42)
- Yildirim, Numan(41)
- Zengin, Gokhan(40)
- Yildirim, Nuran Cikcikoglu(39)
- Ince, Muharrem(37)
- Kocabaş, Mehmet(37)
- Celik, Erkan(35)
- Benzer, Fulya(33)
- Sulaiman, Tukur Abdulkadir(29)
- Aslan, Naim(27)
- Can, Erkan(27)
- Kutlu, Banu(27)
- Kök, Mediha(27)
- Tanyol, Mehtap(27)
- Danabas, Durali(26)
- Kutluyer, Filiz(26)
- Özkul, İskender(26)
- Ates, Mehmet(25)
- Yildirim, Ozal(25)
- Onat, Onur(23)
- Topal, Murat(23)
- Demir, Veysel(22)
- Erten, Fusun(22)
- Guler, Omer(22)
- Say, Yakup(22)
- Yaman, Mehmet(22)
- Alataş, Mevlüt(21)
- Güler, Seval Hale(21)
- Çimen, Okay(21)
- Baykal, Duygu Sen(20)
- Mete, Suleyman(20)
Yayınlar
- MakaleAçık Erişim2019Scopus SJRQ1Side-Channel Analysis of Chaos-Based Substitution Box Structures
Acikkapi, Mehmet Sahin; Ozkaynak, Fatih; Ozer, Ahmet Bedri
There is a theoretically strong relationship between chaos and cryptology. In practice, one of the most successful applications of this relationship is chaos-based s-box structures. However, the performance metrics of chaos-based s-box designs are worse compared to those for s-box structure based on algebraic techniques used in modern encryption algorithms, such as the AES algorithm. What is the reason for using chaos-based s-box structures, even though they have worse cryptographic characteristics? Researchers claim that they may be an alternative defense against implementation attacks, especially side-channel analyses. However, no studies have supported or refuted this claim so far. In this paper, side-channel analyses have been performed for two different chaos-based s-box structures. These two s-box structures have been selected for having with the best and worst performance measurements for s-box structures previously proposed in the literature. The results were compared with the AES s-box structure. Analysis of the results showed that chaos-based s-box structures are more resistant against side-channel attacks. Therefore, chaos-based designs may be an alternative defense against implementation attacks, as alleged. However, both algebraic and chaos-based s-box designs have been observed to be insecure if the attacker has more than 30 plaintexts in the side channel analyses. These results show that implementation analysis studies are required in the chaos-based cryptology literature.
AtıfScopus48WoS42OpenAlex51
İncele - MakaleAçık Erişim2019Scopus SJRQ2The effect of water parameters and dissolved minerals on the hematological parameters of during breeding period catfish (Silurus glanis)
Küçükgül, Azime; Yüngül, Mücahit; Kahraman, Zuhal; Dörücü, Mustafa
In this study, the blood parameters of catfish (Silurus glanis Linnaeus, 1758) inhabiting Celik Lake (Adiyaman, Turkey) were investigated. The study was conducted between April 2013 and October 2013. After obtaining a blood sample from each catfish has been hematologically analyzed. Then, the water temperature, dissolved oxygen, pH, calcium, magnesium and nitrate values were determined at before breeding (April), breeding period (June-July) and after breeding of fish (October) and the impacts of these data on hematological values were investigated. According to this study, it was observed that the hematological values obtained at before breeding period, breeding and after the breeding period were affected by the water quality parameters.
AtıfScopus4WoS6OpenAlex5İncele - MakaleYalnız künye2019Scopus SJRQ2The Evaluation of Imidacloprid Remediation in Soil Media by Two Bacterial Strains
Erguven, Gokhan Onder; Yildirim, Numan
Imidacloprid (C9H10ClN5O2) is used as the most recommended type of insecticide in vegetable farming worldwide. Two types of bacteria (Methylobacterium radiotolerans and Microbacterium arthrosphaerae) were isolated from a corn farming field in the Thrace region of Turkey, and then consortia of these bacteria were prepared from equal volumes of 107 CFU/ml for each bacterium type. Imidacloprid remediation studies were carried out during 18 days in soil test units. The water filtered from these soil test units was determined for chemical oxygen demand (COD) and biochemical oxygen demand (BOD5) to determine the optimum concentration of microorganisms to ascertain the best removal efficiency of Imidacloprid. COD removal rates were 98.7%, 96.4% and 51.6% with 80, 40, and 20 ml volumes of the consortia of bacteria, respectively, at the end of 18 days. The BOD5 removal rates were 88.4%, 78.6% and 49.9% in the same volumes of bacteria, respectively. As a result of this study, we have found that this bacterial consortium is very effective for the bioremediation of this insecticide at the two volumes of 40 and 80 ml, both being better than 20 ml.
AtıfScopus35WoS34OpenAlex37
İncele - MakaleAçık Erişim2019Scopus SJRQ2A deep learning model for automated sleep stages classification using PSG signals
Yildirim, Ozal; Baloglu, Ulas Baran; Acharya, U Rajendra
Sleep disorder is a symptom of many neurological diseases that may significantly affect the quality of daily life. Traditional methods are time-consuming and involve the manual scoring of polysomnogram (PSG) signals obtained in a laboratory environment. However, the automated monitoring of sleep stages can help detect neurological disorders accurately as well. In this study, a flexible deep learning model is proposed using raw PSG signals. A one-dimensional convolutional neural network (1D-CNN) is developed using electroencephalogram (EEG) and electrooculogram (EOG) signals for the classification of sleep stages. The performance of the system is evaluated using two public databases (sleep-edf and sleep-edfx). The developed model yielded the highest accuracies of 98.06%, 94.64%, 92.36%, 91.22%, and 91.00% for two to six sleep classes, respectively, using the sleep-edf database. Further, the proposed model obtained the highest accuracies of 97.62%, 94.34%, 92.33%, 90.98%, and 89.54%, respectively for the same two to six sleep classes using the sleep-edfx dataset. The developed deep learning model is ready for clinical usage, and can be tested with big PSG data.
AtıfScopus255OpenAlex265İncele - MakaleAçık Erişim2019Scopus SJRQ2Automated Depression Detection Using Deep Representation and Sequence Learning with EEG Signals
Ay, Betul; Yildirim, Ozal; Talo, Muhammed; Baloglu, Ulas Baran; Aydin, Galip; Puthankattil, Subha D.; Acharya, U. Rajendra
Depression affects large number of people across the world today and it is considered as the global problem. It is a mood disorder which can be detected using electroencephalogram (EEG) signals. The manual detection of depression by analyzing the EEG signals requires lot of experience, tedious and time consuming. Hence, a fully automated depression diagnosis system developed using EEG signals will help the clinicians. Therefore, we propose a deep hybrid model developed using convolutional neural network (CNN) and long-short term memory (LSTM) architectures to detect depression using EEG signals. In the deep model, temporal properties of the signals are learned with CNN layers and the sequence learning process is provided through the LSTM layers. In this work, we have used EEG signals obtained from left and right hemispheres of the brain. Our work has provided 99.12% and 97.66% classification accuracies for the right and left hemisphere EEG signals respectively. Hence, we can conclude that the developed CNN-LSTM model is accurate and fast in detecting the depression using EEG signals. It can be employed in psychiatry wards of the hospitals to detect the depression using EEG signals accurately and thus aid the psychiatrists.
AtıfScopus279OpenAlex291İncele - MakaleAçık Erişim2019Scopus SJRQ1Al-doped ZnO as a multifunctional nanomaterial: Structural, morphological, optical and low-temperature gas sensing properties
Aydın, Handan; Yakuphanoglu, Fahrettin; Aydın, Cihat
In this study, zinc oxide thin films doped with Al at different atomic ratios (0.1%, 0.5%, 1%, 2%, 5%) were prepared using sol-gel spin coating method. Crystal structure, surface morphology, optical properties of the films and their response to ammonia gas were examined. XRD results showed that the ZnO thin films had a hexagonal polycrystalline structure. It was concluded from the calculation of the crystal size and lattice constant of the films that the produced samples were a nanomaterial. Scanning electron microscope (SEM) and atomic force microscope (AFM) images of the samples revealed that the morphology was composed of nanostructured particles and a cluster structure made of the combination of these particles. The optical band gap (Eg) of the prepared films were found within the range of 3.251 eV–3.342 eV by using the optical absorption method. Characteristics of susceptibility against ammonia gas were evaluated depending on the Al dopant. The obtained results showed that the gas response along with the structural, morphological, and optical properties of ZnO thin films changed with Al dopant. The produced thin film samples can be used as a sensor for the detection of ammonia gas in various industrial branches.
AtıfScopus66WoS59OpenAlex76İncele - MakaleYalnız künye2019Scopus SJRQ4ECG BEAT DETECTION and CLASSIFICATION SYSTEM USING WAVELET TRANSFORM and ONLINE SEQUENTIAL ELM
Yildirim, Ozal
Electrocardiogram (ECG) signals consist of data containing measurements of electrical activity in the heartbeats. These signals include relevant information used to detect abnormalities such as arrhythmia. In this study, a recognition system is proposed for detection and classification of heartbeats in ECG signals. Heartbeats in the ECG data were detected by using the wavelet transform (WT) method and these beats are segmented with determined periods. For obtaining distinctive features from the beats, multi-resolution WT is applied to these segmented signals, and wavelet coefficients are obtained from different frequency levels. Feature vectors are generated on these coefficients by using various statistical methods. The proposed recognition system is trained on feature vectors by using the Online Sequential Extreme Learning Machine (OSELM) classifier during the learning phase to automatically recognize the signals. Five different beat types were obtained from the MIT-BIH arrhythmia dataset. The multi-class dataset that includes five classes and the binary-class dataset that includes two classes were created among these beat types. Performance tests of the proposed wavelet-based-OSELM (W-OSELM) method were realized with these two datasets. The proposed recognition system provided 97.29% correct beat detection rate from raw ECG signals. The classification accuracy is 99.44% for the binary-class dataset and 98.51% for the multi-class dataset. Furthermore, the proposed classifier has shown very fast recognition performance on ECG signals.
AtıfScopus25WoS17OpenAlex26İncele - MakaleAçık Erişim2019Scopus SJRQ3On the exact and numerical solutions to the coupled Boussinesq equation arising in ocean engineering
Sulaiman, T.A.; Bulut, H.; Yokus, A.; Baskonus, H.M.
The studies of the dynamic behaviors of nonlinear models arising in ocean engineering play a significant role in our daily activities. In this study, we investigate the coupled Boussinesq equation which arises in the shallow water waves for two-layered fluid flow. The modified exp (- φ(ζ)) -expansion function method is utilized in reaching the solutions to this equation such as the topological kink-type soliton and singular soliton solutions. The interesting 2D and 3D graphics of the obtained analytical solutions in this study are presented. Via one of the reported analytical solutions, the finite forward difference method is used in obtaining the approximate numerical and exact solutions to this equation. The Fourier–Von Neumann analysis is used in checking the stability of the used numerical method with the studied model. The L 2 and L ∞ error norms are computed. We finally present a comprehensive conclusion to this study.
AtıfScopus83OpenAlex108İncele - MakaleAçık Erişim2019Scopus SJRQ2l-Arginine Improves Sperm Motility in Threatened Coruh Trout Salmo coruhensis (Teleostei: Salmonidae)
Kocabaş, Mehmet; Kutluyer, Filiz; Erişir, Mine; Benzer, Fulya
l-arginine is a versatile amino acid and precursor of nitric oxide that provides protection for preventing free radical damage. Herein, experiments were designed to clarify the effect of l-arginine supplementation on the sperm motility of a threatened trout, Coruh trout Salmo coruhensis. Activation solution was supplemented with levels of 0 mM (Control), 2 mM, 4 mM, and 8 mM l-arginine, and motility and survival of sperm cells were assessed. The selected concentrations were determined according to results of our preliminary experiments. The sperm motility rates at l-arginine concentrations of 0, 2, 4, and 8 mM were 73.33 ± 5.77%, 76.67 ± 5.75%, 80.01 ± 0.01%, and 90.00 ± 0.05%, respectively; notility durations were 21.67 ± 2.08, 32.33 ± 3.79, 32.67 ± 1.15, and 37.00 ± 6.38 s, respectively. Significant effect of l-arginine supplementation was determined on the percentage and duration of motile spermatozoa (p < 0.05). The maximum increment was evoked at the greatest concentration (8 mM). Here, we showed that l-arginine supplement can improve sperm motility of S. coruhensis.
AtıfScopus1WoS1OpenAlex2İncele - MakaleAçık Erişim2019Scopus SJRQ3What is the predictive power of visual mathematics literacy perception and its sub-dimensions for geometry success?; [Görsel Matematik Okuryazarlığı Alt Boyutlarının Geometri Başarısını Yordama Gücü Nedir?]
Ilhan, Aziz; Tutak, Tayfun; Celik, Halil Coskun
Purpose: In this study, it was aimed to examine the relationship between the visual mathematics literacy perceptions and its sub-dimension for geometry success levels of prospective teachers. It was also aimed to examine to what extent visual mathematics literacy perception and its sub-dimensions predicted geometry success. Research Methods: This study was designed in accordance with a qualitative, scanning model. The research was carried out with 232 (97 males and 135 females) prospective teachers who studied in Mathematics Education Program at Firat University, Education Faculty, and were selected by simple random sampling method. “Visual Mathematics Literacy Perception Scale” and “Geometry Success Test” were employed in this study as data collection tools. Correlation analysis and multiple regression analysis were used for analyzing the data. Findings: After the data were analyzed, it was determined that there was a positive relationship between the visual mathematics literacy perception and geometry success of prospective teachers. It was also determined that visual mathematics literacy perception is a meaningful predictor of geometry success. Implications for research and practice: Providing trainings on these concepts in the direction of the results, to investigate the concept of perception on other learning areas of mathematics and conducting experimental studies on the perception of visual mathematics literacy are suggested.
AtıfScopus5WoS2OpenAlex7TR Dizin2
İncele - MakaleYalnız künye2019Uptake of some elements with aquatic plants exposed to the effluent of wastewater treatment plant
Tatar, S.; Öbek, E.; Arslan Topal, E.I.; Topal, M.
In this study, in the removal of macro (P, S, Na, K, Ca, Mg) and micro (Sb, Ba, Co, Cu, Fe, Pb, Mn, Hg, Mo, Se, Ag, Zn) elements in the effluent of Elazig Wastewater Treatment Plant, the efficiency of Lemna minor L. and Lemna gibba L. has been studied comparatively. For this aim, fronds of these plants have been adapted to the effluent of the treatment plant that feeds pilot scale reactors. The concentrations of elements in fronds harvested during the working period were analyzed by ICP/MS. The analytical results show that Lemna minor L. has a high accumulation potential for P, Sb, Ba, Co, Fe, Pb, Mn, Hg, Ag and Zn while Lemna gibba L. has a high accumulation potential for S, Na, Ca, Mg, Cu, Mo and Se. The results show that Lemna minor L. and Lemna gibba L. can be used as phytoremediators of wastewater.
AtıfScopus10OpenAlex6İncele - MakaleYalnız künye2019Scopus SJRQ2Evaluation of health risks from exposure to arsenic and heavy metals through consumption of ten fish species
Varol, Memet; Kaya, Gülderen Kurt; Sünbül, Muhammet Raşit
In this study, the levels of 11 heavy metal(loid)s (HMs) were determined in ten different fish species (wild, farmed, freshwater, and marine) frequently consumed in Turkey and compared with the maximum permissible limits (MPLs) established by international standards. Also, human health risks for the consumers were assessed. Among 11 HMs, only Al and Cr levels did not show significant differences among fish species. The highest concentrations of As were found in red mullet, which is a demersal fish. The average concentrations of Cd, Cr, Cu, and Pb in all fish species were below the MPLs, whereas those of Zn in European anchovy and Mediterranean horse mackerel, and that of inorganic As in red mullet exceeded the MPLs. The highest and lowest toxic metal contents (Al, As, Cd, and Pb) were recorded in red mullet and farmed rainbow trout, respectively. The estimated daily intakes of HMs in each fish species were very lower than their corresponding tolerable daily intakes, suggesting the daily intake of HMs through fish consumption would not pose health risks for the consumers. The target hazard quotient for individual HMs and hazard index for combined HMs in fish species were below 1, which indicated that non-carcinogenic health effects are not expected. The carcinogenic risk results revealed that there was a carcinogenic risk from exposure to inorganic As via the consumption of red mullet. Among all investigated fish species, rainbow trout and common carp were safer in terms of both non-carcinogenic and carcinogenic risks from exposure to HMs.
AtıfScopus72WoS63OpenAlex82İncele - MakaleYalnız künye2019Scopus SJRQ1Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry
Gul, Muhammet; Ak, M. Fatih; Guneri, Ali Fuat
Introduction: Underground mining is considered one of the most hazardous industries and is often associated with serious work-related fatalities; this paper addresses job-related hazards and associated risks. Method: A risk assessment approach is proposed (Pythagorean fuzzy environment) and a case study is carried out in an underground copper and zinc mine. Results: Results of the study demonstrate that hazards can be categorized into different risk levels via compromised solutions of the fuzzy approach. Conclusion: The study provides a theoretical contribution by suggesting a Pythagorean fuzzy numbers-based VlseKriterijumska Optimizacija I Kompromisno Resenje (PFVIKOR) approach. Moreover, it contributes to improving overall safety levels of underground mining by considering and advising on the potential hazards of risk management. Practical applications: The proposed approach will improve the existing safety risk assessment mechanism in underground copper and zinc mining.
AtıfScopus184WoS156OpenAlex180İncele - MakaleAçık Erişim2019Scopus SJRQ3Optimization of medical waste routing problem: The case of TRB1 region in Turkey
Mete, Suleyman; Serin, Faruk
A fundamental problem concerning medical waste disposal is the evaluation of the real and potential risks arising from waste with the focus on the risk of infection. Therefore, the optimization of medical waste routing from collection to disposal center can minimize the risk of infection. The routing of medical waste considers significant to determine potential routes and select the route with minimum distance. The management of the medical waste is important decision for environmental sustainability and includes the collection, transportation and disposal of these materials. In this paper, a geographic information system (GIS) solution approach is proposed to determine the best location of disposal center. Proposed approach is applied to medical waste transportation between 167 health institutions (collection centers) and predetermined 5 disposal centers through TRB1 region in Turkey, which consist of Malatya, Elazığ, Bingöl and Tunceli provinces. The results of case study are examined and suggestions for future research are provided.
AtıfScopus7OpenAlex7İncele - MakaleYayıncıda açık erişim2019Scopus SJRQ3An integrated best-worst and interval type-2 fuzzy TOPSIS methodology for green supplier selection
Yucesan, Melih; Mete, Suleyman; Serin, Faruk; Celik, Erkan; Gul, Muhammet
Supplier selection is one of the most important multi-criteria decision-making (MCDM) problems for decision-makers in the competitive market. Today's organizations are seeking new ways to reduce the negative effects they have on the environment and to achieve a greener system. Currently, the concept of green supplier selection has gained great importance for its ability to incorporate environmental or green criteria into classical supplier selection practices. Therefore, in this study, a multi-phase MCDM model based on the best-worst method (BWM) and the interval type-2 fuzzy technique for order preference by similarity to ideal solution (IT2F TOPSIS) is proposed. A case study in a plastic injection molding facility in Turkey was carried out to show the applicability of the proposed integrated methodology. The paper offers insights into decision-making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.
AtıfScopus93WoS85OpenAlex98İncele - MakaleYalnız künye2018CUSTOMER SEGMENTATION BY USING RFM MODEL AND CLUSTERING METHODS: A CASE STUDY IN RETAIL INDUSTRY
Dogan, Onur; Ayçin, Ejder; Bulut, Zeki Atil
Companies need to understand the customers' data better in all aspects. Detecting similarities and differences among customers, predicting their behaviors, proposing better options and opportunities to customers became very important for customer-company engagement. Segmenting the customers according to their data became vital in this context. RFM (recency, frequency and monetary) values have been used for many years to identify which customers valuable for the company, which customers need promotional activities, etc. Data-mining tools and techniques widely have been used by organizations and individuals to analysis their stored data. Clustering, which one of the tasks of data mining has been used to group people, objects, etc. In this paper we propose two different clustering models to segment 700032 customers by considering their RFM values. We detected that the current customer segmentation which built by just considering customers' expense is not sufficient. Hence, models that recommended in this research are expected to provide better customer understanding, well-designed strategies, and more efficient decisions.
AtıfWoS30İncele - MakaleYalnız künye2018Scopus SJRQ3SEASONALLY VARIATIONS OF ARSENIC SPECIES IN CHICKEN MEATS CONSUMED BY TURKISH PEOPLE WITH HG-AAS
Kaya, Gokce; Karaaslan, Nagihan M.; Yaman, Mehmet
The aim in this study is speciation and determination of arsenic in chicken meat matrix. For this purpose, chicken meat samples consumed commonly by Turkish people belonging to five different companies in Turkey were obtained from markets once per 15 days during 14 months. The samples were digested in microwave oven by using both nitric and hydrochloric acid. It was found that microwave digestion method can be used successfully in the speciation analysis of arsenic. The determination and speciation of As in solutions were carried out by hydride generation-atomic absorption spectrophotometry (HG-AAS). From the observed results, concentrations of As (V) were ranged between 3.0-14.0 ng g(-1) (mean 7.3 ng g(-1)) for breast tissues and 3.0-9.0 ng g(-1) (mean 5.1 ng g(-1)) for leg tissues. The concentrations of As (III) in all studied chicken tissues were found lower than the limit of detection (2 ng g(-1)).
AtıfWoS2İncele - MakaleAçık Erişim2018Investigation of Uplift Rate History of the Yuksekova Basin (Southeast Turkey)
Sançar, Taylan
The 90 km long and N50 degrees-60 degrees W oriented right lateral Semdinli Yuksekova Fault Zone (SYFZ) is located at the southeast of the EACP. The most prominent morphotectonic structure of the SYFZ is the Yuksekova Basin that has a long axis striking in NW-SE direction with a length of 38 km and the maximum width of 10 km. In this study, morphometric indices were used to investigate the uplift characteristics of the basin. According to the Mountainfront sinuosity (S-mf) and the ratio of valley-floor width to valley-height index (V-f) calculations along the mountain fronts on the northern and southern margins of the Yuksekova Basin, the faults that delimit the basin margins have high activity, and the uplift rate is not less than 0.5 mm /yr. Spatial distribution of the m/n values of the drainage areas reveals that the SYFZ have driven the rock uplift around the basin rather than the large-scale lithospheric processes. The integral analysis (chi=chi) of the tributaries in the drainage areas located close to the faults that delimit the Yuksekova Basin indicate that the uplift rate of the basin changes over time regardless of the m/n ratio. The integral analyses of lithological units, which are resistant to erosion around the basin, reveal that uplift rate has been changed four times.
AtıfWoS3OpenAlex5İncele - MakaleYayıncıda açık erişim2018THE MILITARY SUPPORT TO THE 1768-1774 OTTOMAN-RUSSIAN WAR FROM DIVANEORMAN DISTRICT AND DIVANEORMAN DISTRICT'S DEMOGRAPHIC FEATURES (Based on the Registry 6445, dated 1773)
Alti, Aziz
The Registry NFS.d. 6445 in the Ottoman Archives that dates back to 1773 indicates provision of human power to the Ottoman-Russian War. This registry which includes neighbourhoods and the three districts of Hezargrad, is composed of 41 pages. This study examines the Divaneorman district, one of the three districts. In order to contribute to the defence of the Tutrakan city in 1773 against the Russians, a total number of 540 people were selected from the Divaneorman district and recorded in this registry. In this respect, the information belonging to the Divaneorman district is evaluated in two categories: First, the information in the registry is explored from a military standpoint. Second, the present data are evaluated in social, economic and cultural terms.
- MakaleYalnız künye2018Scopus SJRQ3ARTIFICIAL NEURAL NETWORKS AS NEW ALTERNATIVE METHOD TO ESTIMATING SOME POPULATION PARAMETERS OF TIGRIS LOACH (OXYNOEMACHEILUS TIGRIS (HECKEL, 1843)) IN THE KARASU RIVER, TURKEY
Ozcan, Ebru Ifakat; Serdar, Osman
In this study, a new method (Artificial Neural Networks) to estimating some population parameters of Tigris loach (Oxynoemacheilus tigris (Heckel, 1843)) collected between 2014 and 2015 in 14 different stations from Karasu River (East Anatolia, Turkey). The total length and weight of the species ranged from 62 to105 mm and from 1.7 to 10.9 g for females and 65 to 100 mm and from 2.4 to 9.8 g for males, respectively. The new maximum length for O. tigris was found to be 105 mm in this study. The length-weight relation of O. tigris was carried out with artificial neural networks (ANNs) and length-weight relationships (LWRs). The results obtained were compared. Length-weight relationships of O. tigris were found as W=0.0049*L-3.29 , R-2 =0.95 for all individuals. According to these values, the growth type of this species was positive allometric (b>3) for all individuals. Regression analysis showed that fish length has high significant correlation with weight (R=0.97, R-2 =0.95, F-1,F-185=31930.3, P<0.001). According to the comparison of the results obtained with MAPE (%), ANNs provide better results than the LWRs. The results of this study could give useful insight that ANNs can be evaluated as an alternative for length-weight relation estimation. The condition factor values (min-max) were observed as 0.680-1.239 for females and 0.699-1.074 for males. No studies have been done before on this species population parameters.
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