박사

Characterization of Stormwater Quality and Prediction of Runoff Pollutants from Various Landuse Sites

논문상세정보
' Characterization of Stormwater Quality and Prediction of Runoff Pollutants from Various Landuse Sites' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • event mean concentration
  • prediction of water quality
  • stormwater pollution
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
9 0

0.0%

' Characterization of Stormwater Quality and Prediction of Runoff Pollutants from Various Landuse Sites' 의 참고문헌

  • Zhao, J. W., Shan, B. Q., and Yin, C. Q. (2007). Pollutant loads of surface runoff inWuhan City Zoo, an urban tourist area. Journal of Environmental Sciences, 19(4), 464-468.
  • Zhang, Z., Fukushima, T., Onda, Y., Mizugaki, S., Gomi, T., Kosugi, K., Hiramatsu, S.,Kitahara, H., Kuraji, K., Terajima, T., Matsushige, K., Tao, F. (2008). Characterization ofdiffuse pollutions from forested watersheds in Japan during storm events - Itsassociation with rainfall and watershed features. Sci. Total Env., 390(1), 215-226.
  • ZareNezhad, B., Aminian, A. (2010). A multi-layer feed forward neural network model foraccurate prediction of flue gas sulfuric acid dew points in process industries. App. Therm. Eng., 30, 692-696.
  • Yusop, Z., Tan, L.W., Ujang, Z., Mohamed, M., and Nasir, K.A. (2005). Runoff quality andpollution loadings from a tropical urban catchment. Water Sci. Techno., 2, 125-132.
  • Yoon, S. W., Chung, S. W., Oh, D. G., Lee, J. W. (2010). Monitoring of non-point sourcepollutants load from a mixed forest land use. J. Env. Sci., 22(6), 801-805.
  • Xuan, L. (ed.), Mumbai, India: IEEE. (ICESD 2011), pp. 301-304.
  • Wu, J. S., Allan, C. J., Saunders, W. L., and Evett, J. B. (1998). Characterization andpollutant loading estimation for highway runoff. J. Envir. Engrg., 124(7), 584- 592.
  • Wu, J. S., Allan, C. J., Saunders, W. L., Evett, J. B. (1998). Characterization andpollutant loading estimation for highway runoff. J. Envir. Eng., 124(7), 584- 592.
  • Wenger, S. J., Roy, A. H., Jackson, C. R., Bernhardt, E. S., Carter, T. L., Filoso, S.,Gibson, C. A., Hession, W. C., Kaushal, S. S., Marti, E., Meyer, J. D., Palmer, M. A.,Paul, M. J., Purcell, A. H., Ramirez, A., Rosemond, A.D., Schofield, K. A., Sudduth, E.
  • Weiss, J., Hondzo, M. (2004). Laboratory measurements of stormwater qualityimprovement in detention ponds. Project Report No. Mn/DOT 2004-21..
  • Weigend, A. S., Rumelhart, D. E., Huberman, B. A. (1990). Predicting the future: Aconnectionist approach. Int. J. Neural Sys., 1(3), 193-209.
  • Water Quality Monitoring Manual for Construction Sites. (2001). Department ofplanning, transport and infrastructure, government of South Australia.
  • Warren, L. A., Zimmerman, A. P. (1994). The influence of temperature and NaCl oncadmium, copper, and zinc partitioning among suspended particulate and dissolvedphases in an urban river. Water Res., 28(9), 1921-1931.
  • Urbonas, Ben. (2007). Intelligent Modeling to Improve Stormwater Management. Int. Conf. Urban Runoff Modeling. Humboldt State Univ., Arcata, CA.
  • U.S. LACDPW. (1997). Stormwater Monitoring Report. Los Angeles CountyDepartment of Public Works Coastal water research project.
  • U.S. EPA. (2008). Handbook for developing watershed TMDLs draft.
  • U.S. EPA. (2005). National management measures to control nonpoint source pollution fromUrban areas. EPA-841-B-05-004.
  • U.S. EPA. (1983). Nationwide Urban runoff program priority pollutant monitoringproject: Summary of findings. NTIS report no. PB 84-175686.
  • U.S EPA. (2005). Stormwater Phase II Final Rule. Public Education and OutreachMinimum Control Measure. EPA-833-F00-005.
  • U. S. EPA. (2008). State and Regional Coastal Management Plans Queensland’s CoastalPolicy, Guideline, EPA Best Practice Urban Stormwater Management Erosion andSediment Control.
  • U. S. EPA. (2003). Developing water quality criteria for suspended and beddedsediments (SABS).
  • U. S. EPA (1983). Results of the Nationwide Urban Runoff Program, Volume 1 - FinalReport. EPA WH-554. Water Planning Division, Washington.
  • U. S EPA. (1999). Basic Turbidity meter Design and Concepts. EP A Guidance Manual(1999). http://www.epa.gov/ogwdw/mdbp/pdf/turbidity/chap_11.pdf
  • Thomas, P. M. (1993). Implementing a regional urban storm water monitoring program. Proceedings of the 1993 Georgia Water Resources Conference.
  • Sun, H., Cornish, P. S., Daniell, T. M. (2001). Turbidity-based Erosion Estimation in aCatchment in South Australia, J. Hydrol., 253(1-4), 227-238.
  • Stotz, G. 1987. Investigations of the properties of the surface water runoff from federalhighways. Sci. of the Total Envir. 59, 329-337.
  • Stormwater monitoring guidelines north of Dundas Street. (2012). North OakvilleMonitoring Program Guidelines Development Engineering Department, Town ofOakville.
  • Stormwater Discharge Monitoring Plan consists of Sampling and Analysis Plan andQuality Assurance Project Plan. (2012). Water Pollution Control Facilities (WPCF), Cityof Portland.
  • Stein, E.D. Comparison of Stormwater Pollutant Loading by Land Use Type; SouthernCalifornia Coastal Water Research Project, AR08-015-027, 2008.
  • Stein, E. D., Tiefenthaler, L. L., SchiffRandall, K. C. (2008). Comparison of stormwaterpollutant loading by land use type. Southern California Coastal Water Research Project,Annual Report, pp. 15-27.
  • Smullen, J. T., Shallcross, A. L., Cave, K. A. (1999). Updating the US nationwide urbanrunoff quality data base. Wat. Sci .Tech., 39, 9-16.
  • Singh, K. P., Basant, A., Malik, A., Jain, G. (2009). Artificial neural network modeling ofthe river water quality-A case study. Ecol Model., 220, 888?895
  • Shuster, W. D., Bonta, J., Thurston, H., Warnemuende, E., Smith, D. R. (2005). Impacts ofimpervious surface on watershed hydrology: A review. Urban Water J., 2(4), 263-275.
  • Shumway, R. H., Azari, A. S., Kayhanian, M. (2002). Statistical approaches to estimatingmean water quality concentrations with detection limits. Env. Sci. Technol., 36(15),3345-3353.
  • Sharma, D., Gupta, R., Singh, R.K., Kansal, A. (2012). Characteristics of the event mean112concentration (EMCs) from rainfall runoff on mixed agricultural land use in theshoreline zone of the Yamuna River in Delhi, India. Applied Water Science., 2(1), 55-62.
  • Schueler, T. R., Fraley-McNeal, L., Cappiella, K. (2009). Is impervious cover stillimportant? Review of recent research. J. Hydrol. Eng., 14(4), 309-315.
  • Schueler, T. R. (1994). The importance of imperviousness. Watershed ProtectionTechniques, 1(3), 100-111.
  • Schilling, W., Fuchs, L. (1986). Errors in stormwater modelling- A quantitativeassessment. J. Hydraulic Eng., 112(2), 111-124.
  • Schalkoff, R. J. (1997). Artificial Neural Networks McGraw-Hill Higher EducationISBN: 007057118X.
  • Sarukkalige, P. (2011). Characteristics of stormwater runoff in different land use areas. In:International Conference on Environmental Science and Development, Baby, S.,
  • Sartor, J. D., Boyd, G. B. (1972). Water pollution aspects of street surface contaminants. U.S. EPA. EPA-R2-72-081.
  • Russell, S. J., Norvig, P. (2003). Artificial Intelligence: A modern approach PrenticeHall.
  • Rogers, L. L., Dowla, F. U. (1994). Optimization of groundwater remediation usingartificial neural networks with parallel solute transport modeling. Water Res. Res. 30(2),457-481.
  • Rhee, H. P., Yoon, C. G., Lee, S. J., Choi, J. H., Son, Y. K. (2012). Analysis of nonpointsource pollution runoff from urban land uses in South Korea. Environ. Eng. Res., 17(1),47-56.
  • Randall J. C., Barrett, M. E. (1998). Evaluation of methods for estimating stormwaterpollutant load. Water Environ Res., 70, 1295-1302.
  • Priddy K. L., Keller, P. (2005). Artifical Neural Networks an Introduction. Chapter 7, pp. 44-45.
  • Platts, W. S., Torquemada, R. J., Mchenry, M. L., and Graham C. K., (1989). Changes insalmon spawning and rearing habitat from increased delivery of fine sediment to theSouth Fork Salmon River, Idaho, Transactions of the American Fisheries Society.,118(3), 274?283.
  • Paule, M. A., Memon, S. A., Lee, B.-Y., Umer, S. R., Lee, C.-H. (2014). Stormwaterrunoff quality in correlation to land use and land cover development in Yongin, SouthKorea. Water Sci.Technol. 70(2), 218-225.
  • Patil, S. S., Barfield, B. J., Wilber, G. G. (2011). Turbidity modeling based on theconcentration of total suspended solids for stormwater runoff from construction anddevelopment sites. World Environmental and Water Resources Congress 2011: BearingKnowledge for Sustainability - Proceedings of the 2011 World Environmental and WaterResources Congress, pp. 477-486.
  • Osman A. A., Zakaria, M. N., Sulaiman, S., Fatimah W., Ahmad, W. (2010). AComparison of feed-forward back-propagation and radial basis artificial neuralnetworks: a monte carlo study. 978-1-4244-6716-7/10.
  • Ongley, E. D. (1996). Control of water pollution from agriculture. ISSN: 0254-5264.
  • Old, G. H., Leeks, G. J., Packman, J. C., Smith, B. P., Lewis, S., Hewitt, E. J., Holmes, M. and Young, A. (2003). The impact of a convectional summer rainfall event on river flowand fine sediment transport in a highly urbanised catchment Bradford, WestYorkshire, Sci Total Environ., 314, 495?512.
  • Neary, V. S., Neel, T. C., Dewey, J. B. (2002). Pollutant Washoff and Loading fromParking Lots in Cookeville, Tennessee. Global Solutions for Urban Drainage, 1-14
  • Nazahiyah, R., Yusop, Z., and Abustan, I. (2007). Stormwater quality and pollutionloading from an urban residential catchment in Johor, Malaysia. Water Sci. Techno., 56,1-9.
  • Moxness (1988). Characteristics of urban freeway runoff, phase III. Water Quality Unit,111Environmental Services Section, Office of Technical Support, Minnesota Department ofTransportation, St. Paul, MN, USA.
  • Minton, G. R. (2004). Evaluation of the stormwater management stormfilter treatment datavalidation report, 29.
  • Ministry of Environment. (2006). Nonpoint source pollution management handbook. Gwacheon: Ministry of Environment.
  • Memon, S., Go S., Lee, C. H. (2013). Evaluation of first flush phenomenon from bridgeand parking lot sites in the Gyeongan watershed in Korea. Water Environ. Res., 85(3),203-210.
  • Masters, T. (1993). Practical Neural Network Recipes in C 1 1. Academic Press, SanDiego, CA.
  • Massoudieh, A. Kayhanian. (2008). Use of artificial neural networks in predictinghighway runoff constituent event mean concentration. Sci. Iran.,15(3), 308.
  • Maren, A., Harston, C., Pap, R. (1990). Handbook of neural computing applications. Academic Press, San Diego, California.
  • Maniquiza, M. C., Leea, S., Minb, K.-S., Kimc, J. H., Kima, L.-H. (2012). Diffusepollutant unit loads of various transportation landuses. Desal. Water Treat., 38(1), 308-315.
  • Maniquiz, M. C., Lee, S.-Y., Kim, L.-H. (2010). Long-term monitoring of infiltration trenchfor nonpoint source pollution control. Water Air Soil Poll., 212(1-4), 13-26.
  • Maniquiz, M. C., Choi, J., Lee, J., Lee, B.-S., Kim, L.-H. (2010). Application of astructured infiltration system for stormwater management in Campus. Low ImpactDevelopment: Redefining Water in the city., 508-521.
  • Maier, H. R., Dandy, G. C. (2000). Neural networks for the prediction and forecasting ofwater resources variables: a review of modelling issues and applications. Envir. Model. Soft., 15, 101-124.
  • Lischeid, G. (2001). Investigating short-term dynamics and long-term trends of SO4 in therunoff of a forested catchment using artificial neural networks. J. Hydrol., 243, 31-42.
  • Lewis, J. (1996). Turbidity-controlled Suspended Sediment Sampling for Runoff-event LoadEstimation, Water Resour Res., 32(7), 2299-2310.
  • Legret, M., Pagotto, C. (1999). Evaluation of pollutant loadings in the runoff water from amajor rural highway. Sci. Tot. Environ., 235, 143-150.
  • Lee, J. Y., Kim, H., Kim, Y., Han, M. Y. (2011). Characteristics of the event meanconcentration (EMC) from rainfall runoff on an urban highway. Environ. Pollut., 159(4),884-888.
  • Lee, J. H., Bang, K. W., Ketchum, L. H., Choe, J. S. and Yu, M. J. (2002). First flushanalysis of urban storm runoff. Science of total environment, 293, 163-175.
  • Lee, J. H., Bang, K. W. (2000). Characterization of urban stormwater runoff. Wat. Res.,34(6), 1773-1780.
  • Law, N. L. Fraley-McNeal, L., Cappiella, K., Pit, R. (2008). Monitoring to DemonstrateEnvironmental Results: Guidance to Develop Local Stormwater Monitoring StudiesUsing Six Example Study Designs.
  • LSRCA Technical Guidelines for Stormwater Management Submissions (2013).
  • Kim, S. S., Kim, J. S., Bang, K. Y., Gwon E. M., Chung, W. J. (2002). The estimation of theunit load and characteristics of non-point source discharge according to rainfall inKyongan watershed. J. Korean Soc. Environ. Eng., 24(11), 2019-2027.
  • Kim, L.H., Ko, S.O., Jeong, S., and Yoon, J. (2007). Characteristics of washed-offpollutants and dynamic EMCs in parking lots and bridges during a storm. Sci. TotalEnviron., 376, 178-184.
  • Kim, G., Yur, J., Kim, J. (2007). Diffuse pollution loading from urban stormwaterrunoff in Daejeon city, Korea. J. Environ. Manag., 85(1), 9-16.
  • Kim, G., Chung, S., Lee, C. (2007). Water quality of runoff from agricultural-forestrywatersheds in the Geum River Basin, Korea. Env Monit and Assess., 134 (1-3), 441-452.
  • Kayhanian, M., Singh, A., Meyer, S. (2002b). Impact of non-detect in water quality data onestimation of constituent mass loading. Water Sci.Technol., 45(9), 219-225.
  • Kassim, A. H. (2001). Urban stormwater management for Malaysia. Working paper105presented on Seminar on Klang River Environmental Improvement.
  • Kartam, N., Flood, I., Tongthong, T. (1994). Integrating knowledge-based systems andartificial neural networks for civil engineering. J. Art. Intell. Eng. Des., Anal. Manufac.,Academic Press.
  • Karimi, B., Menhaj, M. B., Saboori, I. (2010). Multilayer feed forward neural networks forcontrolling decentralized large-scale non-affine nonlinear systems with guaranteedstability. Int. J. Innov. Comput. I. Control ICIC, 6(11), 4825-4841.
  • Jones, P. W., Jeffrey, B. A., Walter, P. K., Hutchon, H. (1992). In: Chemical Deicers and theEnvironment. D’Itri, F. M. (ed.). Environmental impact of road salting. LewisPublications, Boca Raton, Fl. pp. 1-116.
  • Jang, A., Seo, Y., Bishop, P. (2005). The removal of heavy metals in urban runoff bysorption on mulch. Env. Pollution., 133, 117-127.
  • Irvine, K. N., Somogye, E. L. and Pettibone, G. W., (2002). Turbidity, Suspended Solids,and Bacteria relationships in the Buffalo River Watershed. Middle States Geographer.,35, 42?51.
  • Hubicki, T. S., Weatherbe, D. G. (2001). Stormwater Pollution Prevention Handbook,Conservation Toronto and Region.
  • Huber, W. C., Heaney J. P. (1980). Operational models for stormwater qualitymanagement. environmental impact of nonpoint source pollution. Overcash, M. J.,Davidson, J. M. (eds.) Ann Arbor Science Publishers Inc. pp. 397-444.
  • Huber, W. C. (1993). Contaminant transport in surface water. In: Handbook of hydrology. Maidment, D. R. (Ed.). Department of Civil Engineering, Oregon State University,Corvallis, Oregon, USA. ISBN: 0-07-039732-5.
  • Huang, J.L., Du, P.F., Ao, C.T., Lei, M.H., Zhao, D.Q., Ho, M.H., and Wang, Z.S. (2007). Characterization of surface runoff from a subtropics urban catchment. J. Environ. Sci., 19, 148-152.
  • How to do Stormwater Monitoring. (2007). A guide for construction sites Washington StateDepartment of Ecology. Publication # 06-10-020.
  • Hornik, K., Stinchcombe, M., White, H. (1989). Multilayer feedforward networks areuniversal approximates. Neural Network.s, 2, 359-366.
  • Holmberg, M., Forsius, M., Starr, M., Huttunen, M. (2006). An application of artificialneural networks to carbon, nitrogen and phosphorus concentrations in three borealstreams and impacts of climate change, Ecol. Modell., 195, 51-60.
  • Hernandez, L. D. R. (2011). Exploratory analyses of butler county stream team, 2007-2010.
  • Harper, H .H. (1985). Fate of heavy metals from highway runoff in stormwatermanagement systems. Ph.D. Dissertation, University of Central Florida.
  • Hannouche, A., Chebbo, G., Ruban, G., Tassin, B., Lemaire, B. J., Joannis, C. (2011). Relationship between turbidity and total suspended solids concentration within acombined sewer system, Water Sci Technol., 64(12), 2445-2452.
  • Han Y., Lau S.-L., Kayhanian M., Stenstrom M. K. (2006). Characteristics of highway stormwater runoff. Water Environ. Resour., 78(12), 2377-2388.
  • Hall, M. J. (1984). Urban Hydrology. Elsevier Applied Science Publishers: New York, USA.
  • Haejin, H., Stenstrom, M. K. (2003). Identification of land use with water quality data instormwater using a neural network. Water Res., 37(17), 4222-4230.
  • Gupta K., Saul A. J. (1996). Specific Relationships for the First Flush Load in CombinedSewer Flows. Water research, 30(5), 1244-1252.
  • Guidance manual, Stormwater Monitoring Protocols. (2000). California Department of104Transportation. CTSW-RT-00-005.
  • Guidance for Evaluating Emerging Stormwater Treatment Technologies at ConstructionSites Chemical Technology Assessment Protocol - Ecology (CTAPE) (2003). Publication # 03-10-078.
  • Grayson, R. B., Moore, I. D., McMahon, T. A. (1992). Physically based hydrologicmodeling 2: Is the concept realistic? Water Resour. Res., 26, 2659-2666.
  • Gippel, C. J. (1995). Potential of turbidity monitoring for measuring the transport ofsuspended solids in streams, Hydrol Process., 9(1) 83?97.
  • Gasperi, J., Sebastian, C., Ruban, V., Delamain, M., Percot, S., Wiest, L., Mirande, C.,Caupos, E., Demare, D., Diallo M., Saad, M., Schwartz, J. J., Dubois, P., Fratta, C.,Wolff, H., Moilleron, R., Chebbo, G., Cren, C., Millet, M., Barraud, S., Gromaire, M. C. (2014). Micropollutants in urban stormwater: occurrence, concentrations, andatmospheric contributions for a wide range of contaminants in three French catchmentsEnviron. Sci. Pollut. Res., 21, 5267-5281.
  • Francey, M. (2010). Characterizing Urban Pollutant Loads. PhD thesis, Department of CivilEngineering, Monash University, Australia.
  • El-Din., Smith, D. (2002). Neural network model to predict the wastewater inflow113incorporating rainfall events. Water Res., 36(5), 1115-1126.
  • Drapper, D., Tomlinson, R., Williams, P. (2000). Pollutant concentrations in road runoff:Southeast Queensland case study. J. Env. Eng. 126(4), 313-320.
  • Dogan, E., Ates, A., Ceren, Y. E, Eren, B. (2008). Application of Artificial NeuralNetworks to Estimate Wastewater Treatment Plant Inlet Biochemical Oxygen Demand. Environ Prog., 27(4), 439?445.
  • Deletic, A. B., Maksimovic, C. T. (1998). Evaluation of water quality factors in storm runofffrom paved areas. J. Envir. Engg., 124(9), 869-879.
  • Daphne, L. H. X., Utomo, H. D. and Kenneth, L. Z. H, (2011). Correlation betweenTurbidity and Total Suspended Solids in Singapore Rivers, J. Water Sustain., 1(3) 313?322.
  • Construction Site Storm Water Quality Sampling Guidance Manual. (2003). CTSW-RT- 03-116.31.3.
  • Clair T. A., Ehrman J. M. (1996). Variations in discharge and dissolved organic carbon andnitrogen export from terrestrial basins with changes in climate. LIMNOL. Oceanogr.,41(5), 921-927.
  • Chiew, F. H. S., McMahon, T. A. (1998). Estimation of stormwater runoff and diffusepollution loads. HydraStorm 98, 3rd International Symposium on StormwaterManagement, Adelaide, South Australia.
  • Cheung, S. G., Shin, P. K. S. (2005). Size effects of suspended particles on gill damage ingreen-lipped mussel Perna viridis. Marine Poll. Bull., 51(8-12), 801-810.
  • Cheng, S.-j., Wang, R.-y. (2002). An approach for evaluating the hydrological effects of102urbanization and its application. Hydrol. Process., 16, 1403-1418.
  • Charbeneau, R. J., Barrett, M. E. (1998). Evaluation of Methods for EstimatingStormwater Pollutant Loads. Water Environ. Res., 70, 1295-1302.
  • Characklis, G. W., Wiesner, M. R. (1997). Particles, metals, and water quality in runoff fromlarge urban watershed. J. Env. Eng., 123, 753-759.
  • Chang, M., McBroom, M. W., Beasley, R. S. (2004). Roofing as a source of nonpoint waterpollution. J. Env. Manag., 73(4), 307-315.
  • Carltrans stormwater guidance manual. (2013). Chapter 6, Monitoring site selection. California Department of Transportation, Document No. CTSW-OT-13-999.43.01.
  • Carltrans stormwater guidance manual. (2013). Chapter 2, developing the study plan. California Department of Transportation, Document No. CTSW-OT-13-999.43.01.
  • Butler, D., Karunaratne, S. H. P. G. (1995). The suspended solids trap efficiency of theroadside gully pot. Wat. Res., 29(2), 719-729.
  • Brent D. (2010). Prediction of urban stormwater quality at unmonitored catchmentsusing artificial neural networks. PhD Thesis University of Wollongong.
  • Bowers, J. A., Shedrow, C. B. (2000). Predicting stream water quality using artificial110neural networks. Westinghouse savannah River Company, SRS Ecology EnvironmentalInformation Document, MS, Department of Energy.
  • Bertrand-Krajewski, J. L., Scrivener, O. (1993). Sewer sediment production andtransport modelling: A literature review. J. Hydraulic Res., 31(4), 435-460.
  • Bedan, E. S., Clausen, J. C. (2009). Stormwater runoff quality and quantity fromtraditional and low impact development watersheds. J. Am. Water Resour. As., 45(4),998-1008.
  • Barrett, M. E., Irish, L. B. Jr., Malina, J. F., Charbeneau, R. J. (1998). Characterization ofhighway runoff in Austin, Texas area. J. Envir. Eng. 124(2), 131-137.
  • Bannerman, R.T., Legg, A.D., and Greb, S.R. (1996). Quality of Wisconsin stormwater1989?94: U.S. Geological Survey Open-File Report.
  • Baev. K. V. (1998). Biological neural networks: hierarchical concept of brain function. burkhauser, Boston, USA.
  • Arora, A. S., Reddy, A. S. (2013). Multivariate analysis for assessing the quality ofstormwater from different Urban surfaces of the Patiala city, Punjab (India). UrbanWater J., 10(6), 422-433.
  • Arnold, C. L. Jr., Gibbons, C. J. (1996). Impervious surface coverage: The emergence of akey environmental indicator. J. Am. Plann. Assoc., 62(2), 243-259.
  • Amari, S.-i., Murata, N., Muller, K.-R., Finke, M., Yang, H. H. (1997). Asymptoticstatistical theory of overtraining and cross-validation. IEEE Transac. Neural Networks,8(5), 985-996.
  • Akratos, C. S., Papaspyros, J., Tsihrintzis V. (2008). An artificial neural network model anddesign equations for BOD and COD removal prediction in horizontal subsurfaceflow constructed wetlands. Chem Eng J., 143, 96?110.
  • Abyaneh, H. Z. (2014). Evaluation of multivariate linear regression and artificial neuralnetworks in prediction of water quality parameters. J. Env. Health Sci. Eng., 12, 40.
  • Abyaneh, H. Z. (2014). Evaluation of multivariate linear regression and artificial neuralnetworks in prediction of water quality parameters. J Environ Health Sci Eng.,12(40), 1-8.
  • A guide for construction sites. Developing your stormwater pollution prevention plan, EPA-833-R-06-004.
  • A Master thesis submitted to the Faculty of Miami University, Oxford, Ohio.