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| 1 | Deep learning neural networks for spatially explicit prediction of flash flood probability显示文摘Flood probability maps are essential for a range of applications,including land use planning and developing mitigation strategies and early warning systems.This study describes the potential application of two architectures of deep learning neural networks,namely convolutional neural networks(CNN)and recurrent neural networks(RNN),for spatially explicit prediction and mapping of flash flood probability.To develop and validate the predictive models,a geospatial database that contained records for the historical flood events and geo-environmental characteristics of the Golestan Province in northern Iran was constructed.The step-wise weight assessment ratio analysis(SWARA)was employed to investigate the spatial interplay between floods and different influencing factors.The CNN and RNN models were trained using the SWARA weights and validated using the receiver operating characteristics technique.The results showed that the CNN model(AUC=0.832,RMSE=0.144)performed slightly better than the RNN model(AUC=0.814,RMSE=0.181)in predicting future floods.Further,these models demonstrated an improved prediction of floods compared to previous studies that used different models in the same study area.This study showed that the spatially explicit deep learning neural network models are successful in capturing the heterogeneity of spatial patterns of flood probability in the Golestan Province,and the resulting probability maps can be used for the development of mitigation plans in response to the future floods.The general policy implication of our study suggests that design,implementation,and verification of flood early warning systems should be directed to approximately 40%of the land area characterized by high and very susceptibility to flooding. | Mahdi Panahi Abolfazl Jaafari Ataollah Shirzadi Himan Shahabi Omid Rahmati Ebrahim Omidvar Saro Lee Dieu Tien Bui | 2021 | Geoscience Frontiers2021，12，3： | 4 |
| 2 | Image Encryption Using Random Bit Sequence Based on Chaotic Maps显示文摘 | Himan Khanzadi Mohammad Eshghi Shahram Etemadi Borujeni | 2014 | Arabian Journal for Science and Engineering2014，，2： | 1 |
| 3 | Image encryption using random bit sequence based on chaotic maps 显示文摘 | Himan K Mohammad E | 2014 | Arabian Journal for Science and Engineering2014，39，2： | 1 |
| 4 | The US experience with fluoridation显示文摘 | HIMAN A R STERRIT G R REEVES T G | 1996 | Community and Dental Health1996，13，2： | 1 |
| 5 | Preliminary estimate of the cost of ethanol production for SSF technology显示文摘 | HIMAN N D SCHELL D J RILEY C J | 1992 | Appl Biochem Biotechnol1992，3435，： | 1 |
| 6 | Preliminary estimate of the cost of ethanol production for SSF technology显示文摘 | Himan N D Schell D J Riley C J | 1992 | Appl Biochem Biotechnol1992，3435，： | 1 |
| 7 | Study of different fouling mechanisms during membrane clarification of red plum juice显示文摘 | Himan Nourbakhsh Zahra Emam‐Djomeh Hossein Mirsaeedghazi Mahmoud Omid Sohrab Moieni | 2014 | Int J Food Sci Technol2014，，1： | 1 |
| 8 | Flash flood susceptibility mapping using a novel deep learning model based on deep belief network,back propagation and genetic algorithm显示文摘Flash floods are responsible for loss of life and considerable property damage in many countries.Flood susceptibility maps contribute to flood risk reduction in areas that are prone to this hazard if appropriately used by landuse planners and emergency managers.The main objective of this study is to prepare an accurate flood susceptibility map for the Haraz watershed in Iran using a novel modeling approach(DBPGA)based on Deep Belief Network(DBN)with Back Propagation(BP)algorithm optimized by the Genetic Algorithm(GA).For this task,a database comprising ten conditioning factors and 194 flood locations was created using the One-R Attribute Evaluation(ORAE)technique.Various well-known machine learning and optimization algorithms were used as benchmarks to compare the prediction accuracy of the proposed model.Statistical metrics include sensitivity,specificity accuracy,root mean square error(RMSE),and area under the receiver operatic characteristic curve(AUC)were used to assess the validity of the proposed model.The result shows that the proposed model has the highest goodness-of-fit(AUC=0.989)and prediction accuracy(AUC=0.985),and based on the validation dataset it outperforms benchmark models including LR(0.885),LMT(0.934),BLR(0.936),ADT(0.976),NBT(0.974),REPTree(0.811),ANFIS-BAT(0.944),ANFIS-CA(0.921),ANFIS-IWO(0.939),ANFIS-ICA(0.947),and ANFIS-FA(0.917).We conclude that the DBPGA model is an excellent alternative tool for predicting flash flood susceptibility for other regions prone to flash floods. | Himan Shahabi Ataollah Shirzadi Somayeh Ronoud Shahrokh Asadi Binh Thai Pham Fatemeh Mansouripour Marten Geertsema John J.Clague Dieu Tien Bui | 2021 | Geoscience Frontiers2021，12，3： | 1 |
| 9 | Preliminary estimate of the cost of ethanol production for SSF technology显示文摘 | HIMAN N D SCHELL D J RILEY C J | 1992 | Appl Biochem Biotechnol1992，3435，： | 1 |
| 10 | Preliminary estimate of the Cost of Ethanol Production for Stirnultaneous Saccharification and Fermentation Technology显示文摘 | Himan N D Schell D Riley C | 1992 | Biotechnol Appl Biochem1992，3，35： | 1 |
| 11 | SWPT:An automated GIS-based tool for prioritization of sub-watersheds based on morphometric and topo-hydrological factors显示文摘The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner.Hence,this study aimed at developing a user-friendly geographic information system(GIS)tool,Sub-Watershed Prioritization Tool(SWPT),using the Python programming language to decrease any possible uncertainty.It used geospatial-statistical techniques for analyzing morphometric and topohydrological factors and automatically identifying critical and priority sub-watersheds.In order to assess the capability and reliability of the SWPT tool,it was successfully applied in a watershed in the Golestan Province,Northern Iran.Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds.It provided a cost-effective approach for prioritization of sub-watersheds.Therefore,the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed. | Omid Rahmati Mahmood Samadi Himan Shahabi Ali Azareh Elham Rafiei-Sardooi Hossein Alilou Assefa M.Melesse Biswajeet Pradhan Kamran Chapi Ataollah Shirzadi | 2019 | Geoscience Frontiers2019，10，6： | 1 |
| 12 | Prediction of red plum juice permeate flux during membrane processing with ANN optimized using RSM显示文摘 | Himan Nourbakhsh Zahra Emam-Djomeh Mahmoud Omid Hossein Mirsaeedghazi Sohrab Moini | 2014 | Computers and Electronics in Agriculture2014，，： | 1 |
| 13 | Preliminary estimate of the cost of ethanol production for SSF technology 显示文摘 | Himan N D D J Schell C J Riley | 1992 | Appl Biochem Biotechnol1992，35，34： | 1 |
| 14 | Carbonation calcination cycle using high reactivity calcium oxide for carbon ox deseparation from flue gas 显示文摘 | HIMAN S G FAN L S | 2002 | Ind Eng Chem Res2002，41，： | 1 |
| 15 | A Risk-based Competitive Bi-level Framework for Operation of Active Distribution Networks with Networked Microgrids显示文摘This paper presents a risk-based competitive bi-level framework for optimal decision-making in energy sales by a distribution company(DISCO)in an active distribution network(ADN).At the upper level of this framework,the DISCO and a rival retailer compete for selling energy.The DISCO intends to maximize its profit in the competitive market.Therefore,it is very important for the DISCO to make a decision and offer an optimal price for attracting customers and winning the competition.Networked microgrids(MGs)at the lower level,as the costumers,intend to purchase energy from less expensive sources in order to minimize costs.There is a bi-level framework with two different targets.The genetic algorithm is used to solve this problem.The DISCO needs to be cautious,so it uses the conditional value at risk(CVaR)to reduce the risk and increase the probability of making the desired profit.The effect of this index on the trade between the two levels is studied.The simulation results show that the proposed method can reduce the cost of MGs as the costumers,and can enable the DISCO as the seller to win the competition with its rivals. | Himan Hamedi Vahid Talavat Ali Tofighi Reza Ghanizadeh | 2021 | Journal of Modern Power Systems and Clean Energy2021，9，5： | 0 |
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