Evaluation of the root zone water quality model for predicting water and NO3–N movement in an Iowa soil

Evaluation of computer models with field data is required before they can be effectively used for predicting agricultural management systems. A study was conducted to evaluate tillage effects on the movement of water and nitrate–nitrogen (NO3–N) in the root zone under continuous corn (Zea mays L.) production. Four tillage treatments considered were: chisel plow (CP), moldboard plow (MP), no-tillage (NT), and ridge-tillage (RT). The root zone water quality model (RZWQM: V.3.25) was used to conduct these simulations. Three years (1990–1992) of field observed data on soil water contents and NO3–N concentrations in the soil profile were used to evaluate the performance of the model. The RZWQM usually predicted higher soil water contents compared with the observed soil water contents. The model predicted higher NO3–N concentrations in the soil profile for MP and NT treatments in comparison with CP and RT treatments, but the magnitude of simulated NO3–N peak concentrations in the soil profile were substantially different from those of the observed peaks. The average NO3–N concentrations for the entire soil profile predicted by the model were close to the observed concentrations except for ridge tillage (percent difference for CP=+5.1%, MP=+12.8%, NT=+18.4%, RT=−44.8%). Discrepancies between the simulated and observed water contents and NO3–N concentrations in the soil profile indicated a need for the calibration of plant growth component of the model further for different soil and climatic conditions to improve the N-uptake predictions of the RZWQM

Movement of NO3-N and atrazine through soil columns as affected by lime application

Lime (CaCO3) applied to the soil, to minimize or neutralize the soil pH, can influence the fate and transport of other chemicals in soil. This study was conducted to investigate the effect of lime application on the movement of NO3-N and atrazine through soil columns under saturated and unsaturated conditions

An Contemplated Approach for Criminality Data using Mining Algorithm

We propose an approach for the arrangement and execution of bad behavior area and criminal recognizing confirmation for Indian urban groups using data mining frameworks. Our approach is parceled into six modules, to be particular�information extraction (DE), information preprocessing (DP), grouping, Google outline, characterization and WEKA� execution. To begin with module, DE expels the unstructured wrongdoing dataset from various wrongdoing Web sources, in the midst of the season of 2000� 2018. Second module, DP cleans, facilitates and diminishes the removed wrongdoing data into sorted out 5,038 wrongdoing events. We address these events using 35 predefined wrongdoing attributes. Secure measures are taken for the wrongdoing database accessibility. Rest four modules are useful for bad behavior acknowledgment, criminal recognizing evidence and desire, and bad behavior affirmation, independently. Wrongdoing acknowledgment is explored using k-suggests gathering, which iteratively makes two wrongdoing bundles that rely upon equivalent wrongdoing properties. Google portray observation to k-infers. Criminal conspicuous verification and estimate is dismembered using KNN portrayal. Bad behavior check of our results is done using WEKA�. WEKA� checks an exactness of 93.62 and 93.99 % in the course of action of two bad behavior clusters using picked bad behavior attributes. Our approach contributes in the change of the overall population by helping the looking at workplaces in bad behavior area and guilty parties' recognizing confirmation, and in this way decreasing the bad behavior rates. Wrongdoings are a social unsettling influence and cost the overall population to an awesome degree from various perspectives. Any examination that can help in separating and comprehending wrongdoing speedier pays for itself. Crime data mining has the capacity of extricating helpful data and concealed examples from the substantial wrongdoing informational indexes. The crime data mining challenges are getting to be fortifying open doors for the coming years. Since the writing of crime information mining has expanded energetically as of late, it winds up obligatory to build up a diagram of the cutting edge. This orderly survey centers around crime data mining procedures and innovations utilized as a part of past investigations. The current work is grouped into various classifications and is introduced utilizing perceptions. This paper additionally demonstrates a few difficulties identified with crime data research

Economic Dispatch of Power System Optimization with Power Generation Schedule Using Evolutionary Technique

ABSTRACT: This paper presents an algorithm for solving optimal power flow problem through the application of Differential Evolution (DE). Reduction in fuel costs done of power generation by proper load dispatch schedule. So the overall costing of operation of power system can be reduced. The differential evolution algorithm is an evolutionary algorithm that uses a rather greedy and less stochastic method than do classical evolutionary algorithms such as particle swarm optimization (PSO) .Differential Evolution also incorporates an efficient way of self-adapting mutation using small population. The effectiveness of algorithm has been tested for a practical economic dispatch problem on a test system having three generating units. Thermal power generating firms needs to minimize fuel cost, for better profit at the same time it should satisfy system load demand, real, reactive power limit, voltage limit, power transmission limit and other limitations. For generation cost minimization Economic Load Dispatch (ELD) was developed. When cost is the single objective, the power generation may pollute the environment. Thermal electric power could not be generated without pollution but this pollution can be reduced for the sake of good and healthy atmospheric condition. To reduce emission the firm has to spent money, which is burden and reduces the power generating firms profit. These two opposite objectives should be compromised to find optimal operating condition of thermal power plants which may yield minimum fuel cost. Differential Evolution (DE) algorithm is used to solve this complex problem. KEYWORDS: Optimization, Economic load dispatch, Differential Evolution, PSO. I.INTRODUCTION Power utilities try to achieve high operating efficiency to produce cheap electricity. Competition exists in the electricity supply industry in generation and in the marketing of electricity. The operating cost of a power pool can be reduced if the areas with more economic units generate larger power than their load, and export the surplus power to other areas with more expensive units. Benefits thus gained will depend on several factors like the characteristics of a pool, the policies adopted by utilities, types of interconnections, tie-line limits and load distribution in different areas. Therefore, transmission capacity constraints in production cost analysis are important issues in the operation and planning of electric power system