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Comparison of Artificial Neural Networks with Partial Least Squares Regression for Simultaneous Determinations by ICP-AES

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Chinese Journal of Chemistry 2007年第11期25卷 1658-1662页

作者： KHAYATZADEH MAHANI, mohamad CHALOOSI, Marzieh GHANADI MARAGHEH, mohamad KHANCHI, Ali Reza AFZALI, Dariush Faculty of Chemistry Tarbiat Moalem University No. 49 Mofateh Ave. P.O. Box 15815-3587 Tehran Iran Nuclear Science Research School Nuclear Science and Technology Research Institute AEOI P. O. Box 11365-3486 Tehran Iran Faculty of Science Department of Chemistry Shahid Bahonar University Kerman Iran

Simultaneous determination of several elements （U, Ta, Mn, Zr and W） with inductively coupled plasma atomic emission spectrometry （ICP-AES） in the presence of spectral interference was performed using chemometrics methods. True comparison between artificial neural network （ANN） and partial least squares regression （PLS） for simultaneous determination in different degrees of overlap was investigated. The emission spectra were recorded at uranium analytical line （263.553 nm） with a 0.06 nm spectral window by ICP-AES. Principal component analysis was applied to data and scores on 5 dominant principal components were subjected to ANN. A 5-5-5 （input, hidden and output neurons） network was used with linear transfer function after both hidden and output layers. The PI,S model was trained with five latent variables and 20 samples in calibration set. The relative errors of predictions （REP） in test set were 3.75% and 3.56% for ANN and PLS respectively.

关键词： chemometrics artificial neural network partial least square simultaneous determination

A generalized set of correlations for plus fraction characterization

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Petroleum Science 2012年第3期9卷 370-378页

作者： JAMIALAHMADI mohamad ZANGENEH Hossein HOSSEINI Seyed Sajad Petroleum Engineering Department Petroleum University of Technology Chemical & Petroleum Engineering Department Sharif University of Technology

The importance of accurate determination of the critical properties of plus fractions in prediction of phase behaviour of hydrocarbon mixtures by equations of state is well known in the petroleum industry. It has been stated in various papers （Elsharkawy, 2001） that using the plus fraction as a single group in equation of state calculations reduces the accuracy of the results. However in this work it has been shown that using the proper values of critical temperature and pressure for the plus fraction group can estimate the properties of hydrocarbon mixtures, and they are accurate enough to be used in reservoir engineering and enhanced oil recovery calculations. In this paper, a new method is proposed for calculating the critical properties of plus fractions of petroleum fluids. One can use this method either in predicting critical pressure and temperature of single carbon numbers （SCNs） after the splitting process or in predicting critical pressure and temperature of the plus fraction as a single group. A comparison study is performed against Riazi-Daubert correlation （Riazi and Daubert, 1987） and Sancet correlations （Sancet, 2007） for 25 oil samples taken from 14 fields from southwest Iran. The results indicate the superiority of the proposed method to the Riazi-Daubert and Sancet correlations.

关键词： Plus fraction critical properties correlation single carbon number bubble point calculations

A unified latent variable model for contrastive opinion mining

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Frontiers of Computer Science 2020年第2期14卷 404-416页

作者： Ebuka IBEKE Chenghua LIN Adam WYNER mohamad Hardyman BARAWI Department of Computing Science University of AberdeenAberdeen AB243FXUK

There are large and growing textual corpora in which people express contrastive opinions about the same *** has led to an increasing number of studies about contrastive opinion ***,there are several notable issues with the existing *** mostly focus on mining contrastive opinions from multiple data collections,which need to be separated into their respective collections *** addition,existing models are opaque in terms of the relationship between topics that are extracted and the sentences in the corpus which express the topics;this opacity does not help us understand the opinions expressed in the ***,contrastive opinion is mostly analysed qualitatively rather than *** paper addresses these matters and proposes a novel unified latent variable model(contraLDA),which:mines contrastive opinions from both single and multiple data collections,extracts the sentences that project the contrastive opinion,and measures the strength of opinion contrastiveness towards the extracted *** results show the effectiveness of our model in mining contrasted opinions,which outperformed our baselines in extracting coherent and informative sentiment-bearing *** further show the accuracy of our model in classifying topics and sentiments of textual data,and we compared our results to five strong baselines.

关键词： contrastive opinion mining sentiment analysis topic modelling

Improvement of the microstructural features and mechanical properties of advanced high-strength steel DP590 welds

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International Journal of Minerals,Metallurgy and Materials 2021年第6期28卷 1022-1029页

作者： Arian Ghandi Morteza Shamanian mohamad Reza Salmani Jalal Kangazian College of Pardis Materials Engineering SectionIsfahan University of TechnologyIsfahan 84156-83111Iran Department of Materials Engineering Isfahan University of TechnologyIsfahan 84156-83111Iran Engineering&Quality of Auto Steel Division SAIPA GroupTehranIran

The effects of the welding current mode in resistance spot welding on the microstructure and mechanical properties of advanced high-strength steel dual-phase 590(DP590)sheets were *** showed that a rough martensitic structure was formed in the weld zone of the sample welded via the single-pulsed mode,whereas the microstructure in the heat-affected zone consisted of a very rough martensitic microstructure and rough ***,using the secondary pulse mode led to the formation of tempered martensite in the weld *** maximum load and the energy absorption to failure of the samples with the secondary pulsed cycle were higher than those of the samples with the single-pulsed *** shear results indicated that the secondary pulsed mode could significantly change the mode of failure upon shear tension ***,the obtained results suggest that the use of secondary pulsed mode can improve the microstructural feature and mechanical properties of advanced high-strength steel DP590 welds.

关键词： advanced high-strength steel resistance spot welding microstructure mechanical properties

Effects of Lateral Variation in Vegetation and Basin ‘Dome' Shape on Tropical Lowland Peat Stabilisation in the Kota Samarahan-Asajaya Area, West Sarawak, Malaysia

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Acta Geologica Sinica(English Edition) 2014年第3期88卷 894-914页

作者： mohamad Tarmizi mohamad ZULKIFLEY Tham Fatt NG John Kuna RAJ Roslan HASHIM Muhammad Aqeel ASHRAF Department of Geology Faculty of Science University of Malaya Department of Civil Engineering Faculty of Science University of Malaya

Field surveys indicate lateral variation in peat humification levels （von Post） in dominantly occurring fibric,fibric to hemic,sapric and hemie to sapric peats across a gradient from the margin towards the centre of tropical lowland peat ***-peat stabilisation can be enhanced by adding mineral soil fillers （silt,clays and fine sands） obtained from Quaternary floodplain deposits and residual soil （weathered schist）.The unconfined compressive strength （UCS） of the stabilised cement-mineral soil fifler-peat mix increases with the increased addition of selected mineral soil *** variation in the stabilised peat strength （UCS） in the top 0 to 0.5 m layer was found from the margin towards the centre of the tropical lowland peat *** variations in the UCS of stabilised tropical lowland peats along a gradient from the periphery towards the centre of the peat dome are most likely caused by a combination of factors due to variations in the mineral soil or ash content of the peat and horizontal zonation or lateral variation in the dominant species of the plant assemblages （due to successive vegetation zonation of the peat swamp forest from the periphery towards the centre of the tropical lowland peat dome）.

关键词： tropical lowland peat dome/basin mineral soil filler cement-filler-peat stabilisation,topogenic unconfined compressive strength lateral vegetation succession.

Continuous and Discrete Adjoint Approach Based on Lattice Boltzmann Method in Aerodynamic Optimization Part I:Mathematical Derivation of Adjoint Lattice Boltzmann Equations

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Advances in Applied Mathematics and Mechanics 2014年第5期6卷 570-589页

作者： mohamad Hamed Hekmat Masoud Mirzaei Center of Excellence for Design&Simulation of Space Systems K.N.Toosi University of TechnologyTehran891567Iran

The significance of flow optimization utilizing the lattice Boltzmann(LB)method becomes obvious regarding its advantages as a novel flow field solution method compared to the other conventional computational fluid dynamics *** unique characteristics of the LB method form the main idea of its application to optimization *** this research,for the first time,both continuous and discrete adjoint equations were extracted based on the LB method using a general procedure with low implementation *** proposed approach could be performed similarly for any optimization problem with the corresponding cost function and design variables ***,this approach was not limited to flow fields and could be employed for steady as well as unsteady ***,the continuous and discrete adjoint LB equations and the cost function gradient vector were derived mathematically in detail using the continuous and discrete LB equations in space and time,***,new adjoint concepts in lattice space were ***,the analytical evaluation of the adjoint distribution functions and the cost function gradients was carried out.

关键词： Aerodynamic optimization continuous and discrete adjoint approach lattice Boltzmann method

Fuzzy modelling of combustion efficiency and control of excess air flow case study: 320-MW steam unit/ Isfahan Power Plant/Iran

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Clean Energy 2021年第2期5卷 229-242页

作者： Ahmad Kermani Seyed mohamad Kargar Department of Electrical Engineering Najafabad BranchIslamic Azad UniversityNajafabadIran Smart Microgrid Research Center Najafabad BranchIslamic Azad UniversityNajafabadIran

One of the most critical factors affecting boiler efficiency and hazardous-gas-emission reduction is the volume of excess air mixed with fuel.A knowledge-based approach is proposed to model the efficiency of a 320-MW natural-gas-fired steam power plant in Isfahan,Iran by applying fuzzy-modelling techniques to control the boiler *** model is based on fuel and air entering the ***,the fuzzy-model structure is identified by applying the fuzzy rules obtained from an experienced human *** proposed method is then optimized using a genetic algorithm to increase the fuzzy-model *** results indicate that,by applying a genetic algorithm,the precision of the proposed fuzzy model *** error between the actual efficiency of the plant and the output efficiency of the proposed model is *** model is developed by applying the fuzzy rules and modelling-related ***,to optimize the efficiency of the boiler,a fuzzy proportional-integral controller is *** closed-loop control simulations are run by applying both the proposed controller and the manual controller to demonstrate the influence of the suggested *** simulation outcomes indicate that the recommended controller adjusts the excess-air percentage correctly and increases the unit efficiency by 0.70%,significantly reducing fuel consumption.

关键词： boiler modelling excess air fuzzy control genetic algorithm proportional-integral fuzzy controller

Optimal cost and feasible design for gridconnected microgrid on campus area using the robust-intelligence method

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Clean Energy 2022年第1期6卷 59-76页

作者： mohamad Almas Prakasa Subiyanto Subiyanto Department of Electrical Engineering Faculty of EngineeringUniversitas Negeri SemarangSemarang 50229Indonesia

In this paper,a robust optimization and sustainable investigation are undertaken to find a feasible design for a microgrid in a campus area at minimum *** campus microgrid needs to be optimized with further investigation,especially to reduce the cost while considering feasibility in ensuring the continuity of energy supply.A modified combination of genetic algorithm and particle swarm optimization(MGAPSO)is applied to minimize the cost while considering the feasibility of a grid-connected photovoltaic/battery/diesel ***,a sustainable energy-management system is also defined to analyse the characteristics of the *** optimization results show that the MGAPSO method produces a better solution with better convergence and lower costs than conventional *** MGAPSO optimization reduces the system cost by up to 11.99%compared with the conventional *** the rest of the paper,the components that have been optimized are adjusted in a realistic scheme to discuss the energy profile and allocation *** investigation has shown that MGAPSO can optimize the campus microgrid to be self-sustained by enhancing renewable-energy utilization.

关键词： distributed energy and smart grid renewable-energy system optimization MGAPSO algorithm

Comparison of Artificial Neural Networks,Geographically Weighted Regression and Cokriging Methods for Predicting the Spatial Distribution of Soil Macronutrients(N,P,and K)

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Chinese Geographical Science 2017年第5期27卷 747-759页

作者： Samad EMAMGHOLIZADEH Shahin SHAHSAVANI mohamad Amin ESLAMI 1.Department of Water and Soil Engineering Shahrood University of TechnologyShahrood361999-5161Iran

Soil macronutrients(i.e. nitrogen(N), phosphorus(P), and potassium(K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks(ANN) and two geostatistical methods(geographically weighted regression(GWR) and cokriging(CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil(0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration(n = 84) and validation(n = 22). Chemical and physical variables including clay, p H and organic carbon(OC) were used as auxiliary soil variables to estimate the N, P and K contents. Results showed that the ANN model(with coefficient of determination R^2 = 0.922 and root mean square error RMSE = 0.0079%) was more accurate compared to the CK model(with R^2 = 0.612 and RMSE = 0.0094%), and the GWR model(with R^2 = 0.872 and RMSE = 0.0089%) to estimate the N variable. The ANN model estimated the P with the RMSE of 3.630 ppm, which was respectively 28.93% and 20.00% less than the RMSE of 4.680 ppm and 4.357 ppm from the CK and GWR models. The estimated K by CK, GWR and ANN models have the RMSE of 76.794 ppm, 75.790 ppm and 52.484 ppm. Results indicated that the performance of the CK model for estimation of macro nutrients(N, P and K) was slightly lower than the GWR model. Also, the accuracy of the ANN model was higher than CK and GWR models, which proved to be more effective and reliable methods for estimating macro nutrients.

关键词： precision agriculture soil characteristics interpolation artificial neural networks geographically weighted regression Cokriging