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Information Processing in Agriculture 2016年第3期3卷 133-145页

作者： s.M.shafaei A.Nourmohamadi-Moghadami s.kamgar Department of Biosystems Engineering College of AgricultureShiraz UniversityShiraz 71441-65186Iran

Friction coefficients(static friction coefficient(sFC)and dynamic friction coefficient(DFC))of pomegranate seed on different structural surfaces(glass,aluminum,plywood,galvanized steel and rubber)as affected by moisture content(4-21.9%(d.b.))and sliding velocity(1.4-16(cm/s))were *** of variance(ANOVA)was performed to determine the effect of main treatments and their interactions on sFC and *** of single or multiple effect of the main treatments with five levels was assessed using Duncan’s multiple range test(DMRT).To predict sFC and DFC,multiple linear regression(MLR)modeling technique was applied for each type of structural *** goodness of fit of each MLR model was evaluated using statistical parameters:coefficient of determination,root mean square error and mean relative deviation *** showed that the minimum and maximum sFC or DFC were in minimum and maximum moisture content on glass and rubber surface,*** table indicated the significant effect of main treatments and their interactions on sFC and DFC at significance level of 1%(Psults,sFC linearly increased as moisture content increased and DFC increased also linearly as individual or simultaneous increment of moisture content and sliding velocity occurred,for all experimental *** to the obtained statistical parameters,both sFC and DFC were properly predicted by means of MLR modeling technique.

关键词： Duncan’s multiple range test Analysis of variance Multiple linear regression technique Moisture content sliding velocity

Benchmark of an intelligent fuzzy calculator for admissible estimation of drawbar pull supplied by mechanical front wheel drive tractor

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Artificial Intelligence in Agriculture 2020年第1期4卷 209-218页

作者： s.M.shafaei M.Loghavi s.kamgar Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran

This paper proposes a calculator for estimation of drawbar pull supplied bymechanical front wheel drive tractor based on nominal input variable of tractor drivingmode in two-wheel drive(2WD)and four-wheel drive(4WD),and numeral input variables of tractor weight(53.04–78.45 kN)and slip of driving wheels(1.4–15.1%)utilizing intelligent fuzzy *** systemswere developed bymeans of various input membership functions,output membership functions,defuzzification methods,and training *** prominent developed system for estimation of the drawbar pull yielded a user-friendly intelligent fuzzy calculator with admissible accuracy(coefficient of determination=0.993).Data obtained from the calculator revealed increasing nonlinear trend of the drawbar pull in range of 12.9–57.5 kN as concurrent augment of slip of the wheels and tractor weight,for 2WD *** case of the 4WD mode,it nonlinearly raised from 12.8 to 77.7 ***,effect of the slip and weight on the drawbar pull was found ***,the drawbar pull ranges elucidated that the drawbar pull proliferated as the 4WD mode was employed rather than the 2WD ***,benchmark of the prominent developed intelligent fuzzy system,not only provide simple calculator with the widest applicability for different tractormodels,but also produces added values in enrichment of realization level in domain of tractor drawbar pull concepts.

关键词： Drawbar power Drawbar pull Power efficiency Wheel slip Gross traction force

Feasibility of implementation of intelligent simulation configurations based on data mining methodologies for prediction of tractor wheel slip

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Information Processing in Agriculture 2019年第2期6卷 183-199页

作者： s.M.shafaei M.Loghavi s.kamgar Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran

This paper deals with implementation of intelligent simulation configurations for prediction of tractor wheel slip in tillage *** effects of numeral variables of forward speed(2,4,and 6 km/h)and plowing depth(10,20,and 30 cm),and nominal variable of tractor driving mode(two-wheel drive(2WD)and four-wheel drive(4WD))on tractor rear wheel slip were intelligently simulated utilizing data mining methodologies of artificial neural network(ANN)and adaptive neuro-fuzzy inference system(ANFIs).Neuro-fuzzy potential of the ANFIs simulation framework against neural ability of the ANN simulation framework was *** confirmed higher efficiency of the best configuration of the ANFIs simulation framework with satisfactory statistical performance criteria of coefficient of determination(0.981),root mean square error(1.124%),mean absolute percentage error(1.515%),and mean of absolute values of prediction residual errors(1.135%)than that of the ANN simulation *** perception obtained from the ANFIs simulation results demonstrated that the wheel slip increased nonlinearly with increment of forward speed and plowing depth,while it decreased as tractor driving mode changed from the 2WD to ***,the best configuration of the ANFIs based intelligent simulation framework implemented in this study can be used for further relevant studies of tractor rear wheel slip as a reference.

关键词： Forward speed Plowing depth Tractor driving mode Tillage operations Tractor tractive efficiency

On the neurocomputing based intelligent simulation of tractor fuel efficiency parameters

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Information Processing in Agriculture 2018年第2期5卷 205-223页

作者： s.M.shafaei M.Loghavi s.kamgar Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran

Tractor fuel efficiency parameters(TFEPs)(fuel consumption per working hour(FCWH),fuel consumption per tilled area(FCTA)and specific volumetric fuel consumption(sVFC))were intelligently simulated.A neurocomputing based simulation strategy(adaptive neurofuzzy inference system(ANFIs))was used to simulate the TFEPs.A comparison was also made between results of the best ANFIs environment and those of another neurocomputing based simulation strategy,artificial neural network(ANN).Field experiments were conducted at plowing depths of 10,20 and 30(cm)and forward speeds of 2,4 and 6(km/h)using a disk plow *** descriptor parameters applied to evaluate simulation environments indicated that the best simulation environment of both ANFIs and ANN were able to perfectly predict the ***,the best comprehensive ANN simulation environment with a simple architecture of 2-6-3 was easier to use than three individual ANFIs simulation *** ANN results revealed that simultaneous increase of forward speed from 2 to 6(km/h)and plowing depth from 10 to 30(cm)led to nonlinear increment of the FCWH from 5.29 to 14.89(L/h)and nonlinear decrement of the sVFC from 2.95 to 0.67(L/h kW).Meanwhile,forward speed increment along with plowing depth decrement resulted in nonlinear decrement of the FCTA from 28.13 to 12.24(L/ha).Interaction of forward speed and plowing depth on the FCWH and sVFC was congruent,while it was incongruent for the *** is suggested to employ the ANN environment in developing future fuel planning schemes of tractor during tillage operations.

关键词： Adaptive neuro-fuzzy inference system Artificial neural network Fuel consumption per working hour Fuel consumption per tilled area specific volumetric fuel consumption

Prognostication of energy indices of tractor-implement utilizing soft computing techniques

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Information Processing in Agriculture 2019年第1期6卷 132-149页

作者： s.M.shafaei M.Loghavi s.kamgar Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran

Energy indices(energy requirement for tillage implement(ERTI)and tractor overall energy efficiency(TOEE))of tractor-implement during tillage operations were aimed to be investigated in this *** generate a new comprehensive model,the effects of forward speed at three levels(2,4 and 6 km/h)and plowing depth at three levels(10,20 and 30 cm)on energy indices were experimentally *** soft computing techniques,artificial neural network(ANN)and adaptive neuro-fuzzy inference system(ANFIs),were employed to prognosticate energy *** between the best developed structure of each soft computing technique demonstrated that one comprehensive ANN model was preferred than two individual ANFIs *** to the ANN prognostication results,simultaneous increase of forward speed from 2 to 6 km/h along with plowing depth increment from 10 to 30 cm led to nonlinear increment of the ERTI and TOEE from 33.87 to 122.66 MJ/ha and 4.65 to 17.85%,***,interaction of forward speed and plowing depth on energy indices was *** of comprehensive ANN model now makes it possible to answer fundamental questions in domain of the effect of plowing depth and forward speed on energy indices of tractor-implement that were previously ***,to properly manage energy indices and reduce energy dissipation of tractor-implement,application of the new developed ANN model is strongly recommended.

关键词： Artificial neural network Energy requirement for tillage implement Tractor overall energy efficiency Adaptive neuro-fuzzy inference system

Design, development and field assessment of a controlled seed metering unit to be used in grain drills for direct seeding of wheat

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Information Processing in Agriculture 2015年第3期2卷 169-176页

作者： s.kamgar F.Noei-Khodabadi s.M.shafaei Department of Biosystems Engineering College of AgricultureShiraz UniversityShiraz 71441-65186Iran

A newcontrolled seed metering unit was designed and mounted on a common grain drill for direct seeding of wheat(DsW).It comprised the following main parts:(a)a variable-rate controlled direct current motor(DCM)as seed metering shaft driver,(b)two digital encoders for sensing the rotational speed of supplemental ground wheel(sGW)and seed metering shaft and(c)a control box to handle and process the data of the *** to the considered closed-loop control system,the designed control box regularly checked the revolution per minute(RPM)of seed metering shaft,as operation feedback,using its digital encoder *** seeding ratewas determined based on the calculated error signal and output signal of the digital encoder of the sGW.A field with four different levels of wheat stubble coverage(10%,30%,40%and 50%)was selected for evaluation of the fabricated seed metering unit(FsMU).The dynamic tests were conducted to compare the performance of installed FsMU on the grain drill and equipped grain drill with common seed metering unit(CsMU)at three forward speeds of 4,6 and 8(Km/h)for *** of the FsMU assessment demonstrated that an increase in forwardspeed of grain drill(FsGD)and stubble coverage did not significantly affect the seeding rate in the grain drill *** theFsMU reduced the coefficient of variation(CV)by approximately 50%.Consequently,applying the FsMU on the common grain drill led to a desirable seeding rate at different forward speeds of the grain drill and stubble existence.

关键词： Control box seed metering mechanism Forward speed seed drilling Field operation

Development and validation of an integrated mechatronic apparatus for measurement of friction coefficients of agricultural products

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Information Processing in Agriculture 2020年第1期7卷 93-108页

作者： s.M.shafaei A.Nourmohamadi-Moghadami s.kamgar M.Eghtesad Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran Department of solid Mechanics Engineering School of Mechanical EngineeringShiraz UniversityShiraz 71348-51154Iran

An integrated mechatronic apparatus was developed based on tilting plate method in order to precisely measure static friction coefficient(sFC)and dynamic friction coefficient(DFC)of agricultural *** apparatus consisted of two main parts(mechanical and electrical parts).The main element of mechanical part was rotary ***,the electrical part included control,display,goniometer,level controller,rotational power supply,and infrared *** apparatus was initially simulated in simulation environment and practically calibrated to achieve high precision *** appraise performance of the apparatus,the sFC and DFC of three grains were measured on five contact *** were also conducted by means of a typical apparatus operating based on puling force *** statistical descriptor parameters such as mean absolute percentage error(MAPE),average of absolute values of measurement errors(AAVME),maximum of absolute values of measurement errors(MAVME),and correlation coefficient were used to compare accuracy of the apparatus with the typical *** acceptable AAVME(0.9)indicated high accuracy,stability,and efficiency of the apparatus for automatic measurements of the sFC and *** practical point of view,the mechatronic apparatus would be a beneficial tool for experimental,educational,demonstrational,and research works.

关键词： static friction coefficient Dynamic friction coefficient Physical property Friction force

Neural computing efforts for integrated simulation of ultrasound-assisted hydration kinetics of wheat

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Information Processing in Agriculture 2019年第3期6卷 357-374页

作者： s.M.shafaei A.Nourmohamadi-Moghadami H.Rahmanian-Koushkaki s.kamgar Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran Department of Mechanical Engineering of Biosystems Faculty of AgricultureJahrom UniversityJahrom 74135-111Iran

This study is dedicated to examine predictive ability of neural computing environments,based on artificial neural network(ANN)and adaptive neuro-fuzzy inference system(ANFIs)strategies,for integrated simulation of ultrasound-assisted hydration kinetics of wheat *** process was accomplished at five hydration temperatures of 30,40,50,60 and 70C in ultrasonication conditions named control(without ultrasound treatment),Us1(25 kHz,360 W)and Us2(40 kHz,480 W).The hydration temperature,ultrasonication condition,and hydration time were used as input variables and moisture content was taken as output variable in the neural computing simulation *** account of statistical performance criteria,the distinguished ANFIs simulation environment with coefficient of determination of 0.991,root mean square error of 2.478%d.b.,mean relative deviation modulus of 4.301%and average of absolute values of simulation residual errors of 1.863%*** better performed than the distinguished ANN simulation *** ANFIs simulation results showed that individual or simultaneous increment of hydration temperature and hydration time caused nonlinear increment of moisture content at any given ultrasonication ***,physical perception obtained from the integrated ANFIs simulation results indicated congruency effect(sponge and acoustic cavitation)of cutting-edge ultrasound technology on water *** ANFIs simulation results improved the state of art in domain of studying ultrasoundassisted hydration process of ***,the distinguished ANFIs simulation environment is suggested to be served as an effective step towards management of ultrasound-assisted hydration process of wheat in seed priming,flour milling(tempering),making dough,and wet storage processes.

关键词： Moisture content Hydration rate Water absorption Hydration time Hydration temperature

Reliable execution of a robust soft computing workplace found on multiple neuro-fuzzy inference systems coupled with multiple nonlinear equations for exhaustive perception of tractor-implement performance in plowing process

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Artificial Intelligence in Agriculture 2019年第2期2卷 38-84页

作者： s.M.shafaei M.Loghavi s.kamgar Department of Biosystems Engineering School of AgricultureShiraz UniversityShiraz 71441-65186Iran

Tendency towards computer simulations linked to agricultural machinery has enormously increased in recent *** this regard,the principal contribution of current research was to develop soft computing simulation workplaces for performance prognostication of tractor-implement system in plowing *** neurofuzzy strategies based on multiple adaptive neuro-fuzzy inference systems(MANFIs)scenario and the MANFIs coupled with multiple nonlinear equations(MNE)scenariowere executed in ***,neural strategy based on artificial neural network(ANN)scenario was also fulfilled in the *** variables of plowing depth(10–30 cm),forward speed(2–6km/h),and tillage implement type(moldboard,disk,and chisel plow)were considered as theworkplace inputs and ten performance parameters were taken as the workplace *** to the obtained prognostication accuracy,simulation time,and user-friendly configuration of three scenarios(ANN,MANFIs,andMANFIs+MNE),the MANFIs+MNE was recognized as the prominent simulation *** to the MANFIs+MNE workplace results,for each tillage implement,the compound effect of plowing depth and forward speed on some performance parameters(required draft force of implement,tractor rear wheel slip,fuel consumption per working hour,specific volumetric fuel consumption,tractor drawbar power,energy requirement for tillage implement,overall energy efficiency,and tractor tractive efficiency)was nonlinearly ***,it was nonlinearly antagonism in case of specific draft force and fuel consumption per tilled *** MANFIs+MNE workplace simulation results provide opportunity for technical farmer associations involved in the decision-making of agricultural machinerymanagement in order to gain exhaustive fundamental insights into the compound effect of plowing depth and forward speed on performance of tractor-implement systems in plowing process.

关键词： Draft force Wheel slip Fuel consumption Neuro-fuzzy strategies Intelligent simulation

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轴向应变导致柔性电路的裂化研究

电子显微学报 2003年第2期22卷 142-144页

作者：刘虹雯郭海明王业亮高鸿钧刘盛 kamgar A Gleskova H Wagner s 中国科学院物理研究所纳米物理与器件实验室北京100080 1中国科学院物理研究所纳米物理与器件实验室北京100080 DepartmentofPhysics NewJerseyInstituteofTechnology DepartmentofElectricalEngineering PrincetonUniversity

本文研究了在柔性塑料衬底上的均匀的无定形si和siNx 薄膜的裂化规律。结果表明 ,在单轴向拉力应变下 ,虽然衬底仍保持完整 ,但是半导体薄膜破裂为直的并行的阵列。当应变大于一个临界值后 ,裂纹的密度成线性增长。

关键词：柔性电路轴向应变裂化半导体薄膜裂纹宽度原子力显微镜