Assessment of predictive models for chlorophyll-a concentration of a tropical lake

<p>Abstract</p> <p>Background</p> <p>This study assesses four predictive ecological models; Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.</p> <p>Results</p> <p>Same data set was used for models development and the data was divided into two sets; training and testing to avoid biasness in results. FL and RANN models were developed using parameters selected through sensitivity analysis. The selected variables were water temperature, pH, dissolved oxygen, ammonia nitrogen, nitrate nitrogen and Secchi depth. Dissolved oxygen, selected through stepwise procedure, was used to develop the MLR model. HEA model used parameters selected using genetic algorithm (GA). The selected parameters were pH, Secchi depth, dissolved oxygen and nitrate nitrogen. RMSE, r, and AUC values for MLR model were (4.60, 0.5, and 0.76), FL model were (4.49, 0.6, and 0.84), RANN model were (4.28, 0.7, and 0.79) and HEA model were (4.27, 0.7, and 0.82) respectively. Performance inconsistencies between four models in terms of performance criteria in this study resulted from the methodology used in measuring the performance. RMSE is based on the level of error of prediction whereas AUC is based on binary classification task.</p> <p>Conclusions</p> <p>Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. This was followed by FL, RANN, and MLR.</p

Data sharing reveals complexity in the westward spread of domestic animals across Neolithic Turkey

This study presents the results of a major data integration project bringing together primary archaeozoological data for over 200,000 faunal specimens excavated from seventeen sites in Turkey spanning the Epipaleolithic through Chalcolithic periods, c. 18,000-4,000 cal BC, in order to document the initial westward spread of domestic livestock across Neolithic central and western Turkey. From these shared datasets we demonstrate that the westward expansion of Neolithic subsistence technologies combined multiple routes and pulses but did not involve a set 'package' comprising all four livestock species including sheep, goat, cattle and pig. Instead, Neolithic animal economies in the study regions are shown to be more diverse than deduced previously using quantitatively more limited datasets. Moreover, during the transition to agro-pastoral economies interactions between domestic stock and local wild fauna continued. Through publication of datasets with Open Context (opencontext.org), this project emphasizes the benefits of data sharing and web-based dissemination of large primary data sets for exploring major questions in archaeology (Alternative Language Abstract S1)

the international commodity price shocks

This paper proposes a simple panel stationarity test which takes into account structural shifts and cross-section dependency. Structural shifts are modelled as gradual/smooth process with a Fourier approximation. The so-called Fourier panel stationarity test has a standard normal distribution. The Monte Carlo simulations indicate that (i) if the error terms are i.i.d, the test shows good size and power properties even in small samples; and (ii) if the error terms are serially correlated, the test has reasonable size and high power. We re-examine the behavior of the international commodity prices and find out an evidence on the persistence of shocks

Neural network models as a management tool in lakes

A research was made on the potential use of neural network based models in eutrophication modelling. As a result, an algorithm was developed to handle the practical aspects of designing, implementing and assessing the results of a neural network based model as a lake management tool. To illustrate the advantages and limitations of the neural network model, a case study was carried out to estimate the chlorophyll-a concentration in Keban Dam Reservoir as a function of sampled water quality parameters (PO4 phosphorus, NO3 nitrogen, alkalinity, suspended solids concentration, pH, water temperature, electrical conductivity, dissolved oxygen concentration and Secchi depth) by a neural network based model. Alternatively, the same system was solved with a linear multiple regression model in order to compare the performances of the proposed neural network based model and the traditional linear multiple regression model. For both of the models, the linear correlation coefficients between the logarithms of observed and calculated chlorophyll-a concentrations were calculated. The correlation coefficient R, the best linear fit between the observed and calculated values, was evaluated to assess the performances of the two models. R values of 0.74 and 0.71 were obtained for the neural network based model and the linear multiple regression model, respectively. The study showed that the neural network based model can be used to estimate chlorophyll-a with a performance similar to that of the traditional linear multiple regression method. However, for cases where the input and the output variables are not linearly correlated, neural network based models are expected to show a better performance

Dynamics of suicide in Turkey: an empirical analysis

Background: Suicide has become a public mental health problem in Turkey, with the number of deaths increasing: in 1974, the suicide rate was 1.92% for males and 1.31% for females; in 2013 this had risen to 6.22% for males and 2.26% for females.Aims: This study attempts to empirically investigate the behaviour of suicide in Turkey by focusing on sex and cause. We pay special attention to the role of structural shifts in suicide ratios, which may have arisen from the structural changes in Turkish economy during last 2 decades.Methods: We used time series analysis and employed unit root and stationarity tests for the period 1974-2013.Results: The results show that disruption to female suicide and suicidal affairs stemmed from economic problems and business failures have a random walk process. This finding implies that shocks driven by economic issues and shocks toward the female sex have a permanent, long-term impact on suicide.Conclusions: The implication is that the social administration needs to implement relevant, necessary suicide prevention policies for suicides occurring in the female and economic problems groups.C1 [Akyuz, Mert] Ankara Yildirim Beyazit Univ, Dept Econ, Ankara, Turkey.[Karul, Cagin] Pamukkale Univ, Dept Econometr, Denizli, Turkey.[Nazlioglu, Saban] Pamukkale Univ, Dept Int Trade & Finance, Denizli, Turkey

Dynamics of suicide in Turkey: an empirical analysis.

BACKGROUND: Suicide has become a public mental health problem in Turkey, with the number of deaths increasing: in 1974, the suicide rate was 1.92% for males and 1.31% for females; in 2013 this had risen to 6.22% for males and 2.26% for females. AIMS: This study attempts to empirically investigate the behaviour of suicide in Turkey by focusing on sex and cause. We pay special attention to the role of structural shifts in suicide ratios, which may have arisen from the structural changes in Turkish economy during last 2 decades. METHODS: We used time series analysis and employed unit root and stationarity tests for the period 1974-2013. RESULTS: The results show that disruption to female suicide and suicidal affairs stemmed from economic problems and business failures have a random walk process. This finding implies that shocks driven by economic issues and shocks toward the female sex have a permanent, long-term impact on suicide. CONCLUSIONS: The implication is that the social administration needs to implement relevant, necessary suicide prevention policies for suicides occurring in the female and economic problems groups

Life expectancy and trade openness: causality in Latin America

Purpose The aim of this research is to investigate the causal relationship between trade openness (TO) and life expectancy (LE) at birth in Latin American countries over the period of 1980-2014. Design/methodology/approach The bootstrap panel Granger causality test proposed by Emirmahmutoglu and Kose (2011) was used to determine the direction of causality in the presence of cross-sectional dependency and heterogeneity among Latin American countries. Also, four different tests were employed in order to determine the cross-sectional dependency and slope homogeneity. The stationarity properties of variables were inspected by employing a unit root test. Findings The findings indicated that Granger causality existed between TO and LE, at birth which was running from the former to the latter for panel. On a country basis, TO Granger caused LE at birth for countries with low level of economic development and higher taxes on income and profits. Practical implications This study provides new insights for policymaking regarding the role of TO in achieving comprehensive economic reforms to increase LE at birth during a period of intense trade rivalry across nations. Originality/value Although research in the literature has mainly focused on the impact of TO on LE at birth with panel data, most studies ignored the regional effects. It is the authors' concern that the direction of causality can be country-specific and have regional characteristics. In this regard, instead of dividing countries for a specific region into two parts such as developing and developed, the authors investigated the pattern of trade-health link for a specific region, Latin America.C1 [Akyuz, Mert; Demir, Ibrahim] Ankara Yildirim Beyazit Univ, Dept Econ, Ankara, Turkey.[Karul, Cagin] Pamukkale Univ, Dept Econometr, Denizli, Turkey