A multi-objective fuzzy optimization model for cropping structure and water resources and its method

Cropping structure has a close relationship with the optimal allocation of agricultural water resources. Based on the analysis of the relationship between agricultural water resources and sustainable development, this paper presents a multi objective fuzzy optimization model for cropping structure and water allocation, which overcomes the shortcoming of current models that only considered the economic objective,and ignored the social and environmental objectives. During the process, a new method named fuzzy deciding weight is developed to decide the objective weight. A case study shows that the model is reliable, the method is simple and objective, and the results are reasonable. This model is useful for agricultural management and sustainable development.

Multi-objective optimization of process based on resource capability

To improve the practicability, suitability and accuracy of the trade-off among time, cost and quality of a process, a method based on resource capability is introduced. Through analyzing the relationship between an activity and its’ supporting resource, the model trades off the time, cost and quality by changing intensity of labor or changing the types of supporting resource or units of labor of resource in a certain time respectively according to the different types of its’ supporting resources. Through contrasting this method with the model of unit time cost corresponding to different quality levels and inter-related linear programming model of time, cost and quality for process optimizing, it is shown that this model does not only cover the above two models but also can describe some conditions the above two models can not express. The method supports to select different function to optimize a process according to different types of its supporting resource.

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms

This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.

Using LBG quantization for particle-based collision detection algorithm

Most collision detection algorithms can be efficiently used only with solid and rigid objects, for instance, Hierarchical methods which must have their bounding representation recalculated every time deformation occurs. An alternative algorithm using particle-based method is then proposed which can detect the collision among non-rigid deformable polygonal models. However, the original particle-based collision detection algorithm might not be sufficient enough in some situations due to the improper particle dispersion. Therefore, this research presents an improved algorithm which provides a particle to detect in each separated area so that particles always covered all over the object. The surface partitioning can be efficiently performed by using LBG quantization since it can classify object vertices into several groups base on a number of factors as required. A particle is then assigned to move between vertices in a group by the attractive forces received from other particles on neighbouring objects. Collision is detected when the distance between a pair of corresponding particles becomes very small. Lastly, the proposed algo- rithm has been implemented to show that collision detection can be conducted in real-time.

Multi-objective capacity allocation optimization method of photovoltaic EV charging station considering V2G

Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.

Mixed Gl2／GH2 multi-channel multi-objective control synthesis for discrete time systems

This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2 (GH2) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

PERFORMANCE COMPARISON OF A LINEARLY COMBINED ORDERED-STATISTIC DETECTORS UNDER POSTDETECTION INTEGRATION AND NONHOMOGENEOUS SITUATIONS

Several Constant False Alarm Rate （CFAR） architectures, where radar systems often employ them to automatically adapt the detection threshold to the local background noise or clutter power in an attempt to maintain an approximately constant rate of false alarm, have been recently proposed to estimate the unknown noise power level. Since the Ordered-Statistics （OS） based algorithm has some advantages over the Cell-Averaging （CA） technique, we are concerned here with this type of CFAR detectors. The Linearly Combined Ordered-Statistic （LCOS） processor, which sets threshold by processing a weighted ordered range samples within finite moving window, may actually perform somewhat better than the conventional OS detector. Our objective in this paper is to analyze the LCOS processor along with the conventional OS scheme for the case where the radar receiver incorporates a postdetection integrator amongst its contents and where the operating environments contain a number of secondary interfering targets along with the primary target of concern and the two target types fluctuate in accordance with the Swerling Ⅱ fluctuation model and to compare their performances under various operating conditions.

Model-based optical metrology and visualization of 3-D complex objects

This letter addresses several key issues in the process of model-based optical metrology, including three dimensional (3D) sensing, calibration, registration and fusion of range images, geometric representation, and visualization of reconstructed 3D model by taking into account the shape measurement of 3D complex structures,and some experimental results are presented.

Design and optimization in multiphase homing trajectory of parafoil system

In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scenario,on the basis of geometric relationship of each phase trajectory,the problem of trajectory planning is transformed to parameter optimizing,and then auxiliary population-based quantum differential evolution algorithm(AP-QDEA)is applied as a tool to optimize the objective function,and the design parameters of the whole homing trajectory are obtained.The proposed AP-QDEA combines the strengths of differential evolution algorithm(DEA)and quantum evolution algorithm(QEA),and the notion of auxiliary population is introduced into the proposed algorithm to improve the searching precision and speed.The simulation results show that the proposed AP-QDEA is proven its superior in both effectiveness and efficiency by solving a set of benchmark problems,and the multiphase homing scheme can fulfill the requirement of fixed-points and upwind landing in the process of homing which is simple in control and facile in practice as well.

Analogy-based software effort estimation using multi-objective feature selection

The feature selection in analogy-based software effort estimation （ASEE） is formulized as a multi-objective optimization problem. One objective is designed to maximize the effort estimation accuracy and the other objective is designed to minimize the number of selected features. Based on these two potential conflict objectives, a novel wrapper- based feature selection method, multi-objective feature selection for analogy-based software effort estimation （MASE）, is proposed. In the empirical studies, 77 projects in Desharnais and 62 projects in Maxwell from the real world are selected as the evaluation objects and the proposed method MASE is compared with some baseline methods. Final results show that the proposed method can achieve better performance by selecting fewer features when considering MMRE （mean magnitude of relative error）, MdMRE （median magnitude of relative error）, PRED （ 0. 25 ）, and SA （ standardized accuracy） performance metrics.

Estimating the Macroeconomic Costs of CO_2 Emission Reduction in China Based on Multi-objective Programming

This paper estimates the macroeconornic costs of CO2 emission reduction in China employing the input-output analysis with the multi-objective programming approach. The results show that the effect of reducing CO2 emissions on China＇s economy is significant. Under the present conditions, the estimated macroeconomic costs of CO2 emission reduction in 2010 for China are approximately 3,100-4,024 RMB t-1. The stronger the abatement actions, the higher the macroeconomic costs of per unit emission reduction would be. Excavation industry, oil industry, chemical industry, and metal smelting industry have high potential to abate their CO2 emissions.

Kernelized fourth quantification theory for mineral target prediction

This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are ex- pected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quan- tifieation theory onto a low-dimensional scaling space, where the sealed cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the sealed cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly ceils. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional sealing space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.

Explore the application of educational information in College English Teaching

With the development of information technology, it has become a hot topic in higher education sector that integrate IT with other disciplines in university and bring it into the classroom. This paper demonstrates the integration of information technology and interactive college English teaching aiming to improve the efficiency of classroom teaching and the quality of teaching so as to achieve the modernization of education and cultivate modem talents in a better way.

Constructal entransy dissipation rate minimization of a rectangular body with nonuniform heat generation

Based on construtal theory, a nonuniform heat generation problem in a rectangular body is investigated in this paper. Entransy dissipation rate(EDR) is taken as the optimization objective. The optimal body shapes with constant and variable widths of the high conductivity channel(HCC) are derived. For the rectangular first order assembly(RFOA) with constant cross-section HCC, the shape of the RFOA and width ratio of the HCCs are optimized, and the double minimum EDR is obtained. The heat transfer performance of the RFOA becomes worse when the nonuniform coefficient increases. For the RFOA with variable cross-section HCC, the EDR of the RFOA can be minimized for four times. Compared the optimal construct based on minimum EDR of the RFOA with that based on minimum maximum temperature difference, the shape of the former optimal construct is tubbier, and the average temperature difference is lower. In the practical design of electronic devices, when the thermal safety is ensured, the constructal design scheme of the former optimal construct can be adopted to improve the global heat transfer performance of an electronic device.