Neural Network based Predictors for Evaporation Estimation at Jabalpur in Central India

319-328Free water evaporation is an imperative parameter for estimation of crop water requirement, and irrigation scheduling. This study aims to evaluate different techniques to estimate evaporation with weather parameters inputs. Multilayer Perception (MLR), Radial Basis Function (RBF) based neural network, traditional statistical Linear Regression (LR) approach and conventional empirical methods of Linacre and Christianson were used to estimate the evaporation at Jabalpur station situated under Kymore Plateau and Satpura Hills Agro-climatic Zone of Madhya Pradesh in the Central India. The weather parameters considered for estimation of evaporation are temperature, humidity, sunshine hours and wind speed. Results indicate that MLP and RBF based models with input of all selected weather parameters is able to estimate evaporation much precisely than LR and empirical approaches. It was found that higher accuracy may be obtained with multiple weather data input and low accuracy with only temperature input. It was observed that with temperature used as input the performance accuracy reduces in estimating evaporation with the selected models. However, neural network approach seems to produce better results as compared to statistical and empirical approach. The neural network based model RBF found more efficient in estimation of evaporation as compared to MLP. This study suggests that evaporation can be estimated by RBF model of a station, where there is no standard instrument available for its observation

Volatile organic carbon monitoring in indoor environment using a versatile hydrophobic flyash-based zeolite as adsorbent

Volatile organic carbon (VOC) in indoor air is a matter of concern. The conventional adsorbents used for monitoring of VOC's are beset with drawbacks. A new class materials,namely surface modified zeolites (SMZ) has been synthesized from flyash as the source material. SMZ have been used for indoor monitoring of VOCs vis-a-vis conventional adsorbents. The adsorbed VOCs were desorbed at higher temperature and analysed using GC-MS Technique. Thr VOC adsorbed on SMZ are much higher compaired to activated carbon, illustrating the successful usage oF SMZ as novel and versatile adsorbent for VOC monitoring

Experiments on strategic choices and markets

Abstract Much of experimental research in marketing has focused on individual choices. Yet in many contexts, the outcomes of one's choices depend on the choices of others. Furthermore, the results obtained in individual decision making context may not be applicable to these strategic choices. In this paper, we discuss three avenues for further advancing our understanding of strategic choices. First, there is a need to develop theories about how people learn to play strategic games. Second, there is an opportunity to enrich standard economic models of strategic behavior by allowing for different types of bounded rationality and by relaxing assumptions about utility formulation. These new models can help us to more accurately predict strategic choices. Finally, future research can improve marketing practice by designing better mechanisms and validating them using experiments