A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

Modeling urban land use dynamics using Markov-chain and cellular automata in Gondar City,Northwest Ethiopia

Modeling urban land-use dynamics is critical for urban experts’and infrastructure managers’planning.This study attempts to explore the land-use/land-cover(LULC)dynamics of Gondar using satellite images from 1984 to 2020.Markov-Chain and Cellular Automata(MC-CA)models have been recognized as performing well in predicting urban land-use change.However,only a few models work in Ethiopia in general,and no study in Gondar has applied this approach to study urban land-use patterns.Therefore,Gondar land-use/land cover changes of Gondar were predicted using the MC-CA model in IDRISI.The built-up area in Gondar city covered 1413 ha(3%of the total area)in 1984 and increased to 2380 ha(5%)in 1994;21153 ha(45.5%)in 2004;22622 ha(48.7%)in 2014;and 23427 ha(50.5%)in 2020.The area has been predicted to reach 57.5%in the 2050s,showing a faster increase that will cause a very vast loss of farmland.This will increase urban sprawl challenges as well as overall environmental disequilibrium in the preceding decade.Thus,innovative and careful structures and systems in urban planning are required to secure a sustainable urban future and to make our cities livable and competitive in the paradigm of sustainable cities.

A Study on the Factors Influencing Value-Added in the Cruise Ship Value Chain Based on the DEMATEL-ISM Model

Cruise value chain is to take the exchange of cruise products and services as the core in a certain spatial scope,and enterprises with core advantages within or between different industries establish associations in accordance with certain technical and economic conditions,so as to realise the multi-dimensional extension and value appreciation of the cruise value chain in the vertical and horizontal links,and ultimately establish a chain-network type of enterprise strategic alliance.This paper tries to analyse the value-added factors of the cruise industry chain by constructing a multi-level hierarchical structural model with reference to the influencing factor analysis methods of relevant literature-DEMATEL(Decision Making Experiment and Evaluation Experiment)and ISM(Interpretative Structural Model).The study shows that the innovation and scale value-added module in the upstream of the cruise industry chain is the core module of value-added of the whole cruise industry chain,and the value-added mainly originates from the design and manufacturing of cruise ships.The middle reaches of the cruise industry chain are mainly cruise operation enterprises,and the specificity of cruise operation determines that its brand value-added is mainly accomplished through the global layout of multinational corporations,and the cruise brand is able to drive the consumption demand and has value-added ability.The downstream value-added of the cruise industry chain is mainly realised through the increase in profits of cruise tourism service products.

Application of Exponential Distribution in Modeling of State Holding Time in HIV/AIDS Transition Dynamics

Markov modeling of HIV/AIDS progression was done under the assumption that the state holding time (waiting time) had a constant hazard. This paper discusses the properties of the hazard function of the Exponential distributions and its modifications namely;Parameter proportion hazard (PH) and Accelerated failure time models (AFT) and their effectiveness in modeling the state holding time in Markov modeling of HIV/AIDS progression with and without risk factors. Patients were categorized by gender and age with female gender being the baseline. Data simulated using R software was fitted to each model, and the model parameters were estimated. The estimated P and Z values were then used to test the null hypothesis that the state waiting time data followed an Exponential distribution. Model identification criteria;Akaike information criteria (AIC), Bayesian information criteria (BIC), log-likelihood (LL), and R2 were used to evaluate the performance of the models. For the Survival Regression model, P and Z values supported the non-rejection of the null hypothesis for mixed gender without interaction and supported the rejection of the same for mixed gender with interaction term and males aged 50 - 60 years. Both Parameters supported the non-rejection of the null hypothesis in the rest of the age groups. For Gender male with interaction both P and Z values supported rejection in all the age groups except the age group 20 - 30 years. For Cox Proportional hazard and AFT models, both P and Z values supported the non-rejection of the null hypothesis across all age groups. The P-values for the three models supported different decisions for and against the Null hypothesis with AFT and Cox values supporting similar decisions in most of the age groups. Among the models considered, the regression assumption provided a superior fit based on (AIC), (BIC), (LL), and R2 Model identification criteria. This was particularly evident in age and gender subgroups where the data exhibited non-proportional hazards and violated the assumptions required for the Cox Proportional Hazard model. Moreover, the simplicity of the regression model, along with its ability to capture essential state transitions without over fitting, made it a more appropriate choice.

An Evaluation of the Critical Success Factors in Sustainable Food Supply Chains in Developing Countries

Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.

The Operation Mechanism of Agricultural Products Supply Chain and Profit Allocation Model in the Context of Asymmetric Information

The research performed analysis on causes of asymmetric information of agricultural product supply chain and made conclusion on operation mechanism and characteristics of supply chain based on asymmetric information. Finally, the research detailed profit sharing of agricultural product supply chain in the context of asymmetric information and proposed suggestions, providing references of pricing and profit sharing of supply chains of agricultural products.

Applicability of Markov chain-based stochastic model for bubbling fluidized beds

A Markov chain-based stochastic model （MCM） is developed to simulate the movement of particles in a 2D bubbling fluidized bed （BFB）. The state spaces are determined by the discretized physical cells of the bed, and the transition probability matrix is directly calculated by the results of a discrete element method （DEM） simulation. The Markov property of the BFB is discussed by the comparison results calculated from both static and dynamic transition probability matrices. The static matrix is calculated based on the Markov chain while the dynamic matrix is calculated based on the memory property of the particle movement. Results show that the difference in the trends of particle movement between the static and dynamic matrix calculation is very small. Besides, the particle mixing curves of the MCM and DEM have the same trend and similar numerical values, and the details show the time averaged characteristic of the MCM and also expose its shortcoming in describing the instantaneous particle dynamics in the BFB.

The Operation Model of Pig Supply Chain Based on Temporal and Spatial Perspectives

This paper constructed pig supply chain based on theoretical study and practical research, then analyzed the operation model of pig supply chain from tem- poral and spatial perspectives. The results showed that from the spatial perspective, pig supply chain had five models of operation, such as vertical integration pig sup- ply chain, quasi-vertical integration pig supply chain （tightly-knit pig supply chain）, semi-tightly pig supply chain, loosely-organized pig supply chain and market-oriented pig supply chain. In contrast, from temporal aspect, pig supply chain experiences the pure market transaction, contract form, cooperatives, vertical integration and hori- zontal integration model of operation; the future pig supply chain model in China might be the longitudinal transverse group alliance pig supply chain, namely, the upper vertical integration or quasi-vertical integration （leading processing enterprise ＋ farmer） and down horizontal integration （leading processing enterprises ＋ logistics company ＋ sales）, and it would be a kind of competition among interest groups by division of cooperation.

Dynamic Modeling of a Roller Chain Drive System Considering the Flexibility of Input Shaft

Roller chain drives are widely used in various high-speed, high-load and power transmission applications, but their complex dynamic behavior is not well researched. Most studies were only focused on the analysis of the vibration of chain tight span, and in these models, many factors are neglected. In this paper, a mathematical model is developed to calculate the dynamic response of a roller chain drive working at constant or variable speed condition. In the model, the complete chain transmission with two sprockets and the necessary tight and slack spans is used. The effect of the flexibility of input shaft on dynamic response of the chain system is taken into account, as well as the elastic deformation in the chain, the inertial forces, the gravity and the torque on driven shaft. The nonlinear equations of movement are derived from using Lagrange equations and solved numerically. Given the center distance and the two initial position angles of teeth on driving and driven sprockets corresponding to the first seating roller on each side of the tight span, dynamics of any roller chain drive with two sprockets and two spans can be analyzed by the procedure. Finally, a numerical example is given and the validity of the procedure developed is demonstrated by analyzing the dynamic behavior of a typical roller chain drive. The model can well simulate the transverse and longitudinal vibration of the chain spans and the torsional vibration of the sprockets. This study can provide an effective method for the analysis of the dynamic characteristics of all the chain drive systems.

Grey Markov chain and its application in drift prediction model of FOGs

A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantages of grey model and Markov chain. It makes good use of dynamic modeling idea of the grey model to predict general trend of original data. Then according to the trend, states are divided so that it can overcome the disadvantage of high computational cost of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of the grey model and makes it be fit for prediction of random data with bigger fluctuation. The numerical results of real drift data from a certain type FOG verify the effectiveness of the proposed grey Markov chain model powerfully. The Markov chain is also investigated to provide a comparison with the grey Markov chain model. It is shown that the hybrid grey Markov chain prediction model has higher modeling precision than Markov chain itself, which prove this proposed method is very applicable and effective.

Reliability model of organization management chain of South-to-North Water Diversion Project during construction period

In order to analyze the indispensability of the organization management chain of the South-to-North Water Diversion Project （SNWDP）, two basic forms （series connection state and mixed state of both series connection and parallel connection） of the organization management chain can be abstracted. The indispensability of each form has been studied and is described in this paper. Through analysis of the reliability of the two basic forms, reliability models of the organization management chain in the series connection state and the mixed state of both series connection and parallel connection have been set up.

A dynamic optimization model of an integrated coal supply chain system and its application

Various nodes,logistics,capital flows,and information flows are required to make systematic decisions concerning the operation of an integrated coal supply system. We describe a quantitative analysis of such a system. A dynamic optimization model of the supply chain is developed. It has achieved optimal system profit under conditions guaranteeing a certain level of customer satisfaction. Applying this model to coal production of the Xuzhou coal mines allows recommendations for a more systematic use of washing and processing,transportation and sale resources for commercial coal production to be made. The results show that this model,which is scientific and effective,has an important value for making reasonable decisions related to complex coal enterprises.

A new grey forecasting model based on BP neural network and Markov chain

A new grey forecasting model based on BP neural network and Markov chain was proposed. In order to combine the grey forecasting model with neural network, an important theorem that the grey differential equation is equivalent to the time response model, was proved by analyzing the features of grey forecasting model（GM（1,1））. Based on this, the differential equation parameters were included in the network when the BP neural network was constructed, and the neural network was trained by extracting samples from grey system＇s known data. When BP network was converged, the whitened grey differential equation parameters were extracted and then the grey neural network forecasting model （GNNM（1,1）） was built. In order to reduce stochastic phenomenon in GNNM（1,1）, the state transition probability between two states was defined and the Markov transition matrix was established by building the residual sequences between grey forecasting and actual value. Thus, the new grey forecasting model（MNNGM（1,1）） was proposed by combining Markov chain with GNNM（1,1）. Based on the above discussion, three different approaches were put forward for forecasting China electricity demands. By comparing GM（1, 1） and GNNM（1,1） with the proposed model, the results indicate that the absolute mean error of MNNGM（1,1） is about 0.4 times of GNNM（1,1） and 0.2 times of GM（I, 1）, and the mean square error of MNNGM（1,1） is about 0.25 times of GNNM（1,1） and 0.1 times of GM（1,1）.

Stability of the Konjac Glucomannan Topological Chain Based on Quantum Spin Model

In this paper we investigated the stability of konjac glucomnnan（KGM） chain hydrogen networks based on the quantum spin model. Dissipative particle dynamics method was applied in the structure simulation of KGM. The results reveled that acetyl residues of KGM were bonded with water molecules in aqueous solutions. Increasing the hydrogen bond formation decreases the energy in acetyl system. The expect-valuation of the thermal state with respect to the Hamiltonian is negative. Hence, the total energy of konjac glucomnnan chain with the acetyl groups decreases, which indicates the increasing stability of konjac glucomnnan chain. Our approach could provide a new insight into the investigation on the stability of konjac glucomnnan chain.

Analysis of Supply Chain Model of Agricultural Products and Quality Safety——A Case Study of Heilongjiang Province

This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In view of different models,corresponding suggestions are put forward to ensure the quality safety of agricultural products in Heilongjiang Province.

Testing and Evaluation for Web Usability Based on Extended Markov Chain Model

As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can be utilized in the latter stages, which is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (EMM) is to present the error type vector which is treated as a part of page node. this paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented. Key words statistical testing - evaluation for Web usability - extended Markov chain model (EMM) - Web log mining - reliability evaluation CLC number TP311. 5 Foundation item: Supported by the National Defence Research Project (No. 41315. 9. 2) and National Science and Technology Plan (2001BA102A04-02-03)Biography: MAO Cheng-ying (1978-), male, Ph.D. candidate, research direction: software testing. Research direction: advanced database system, software testing, component technology and data mining.

MODELING THE CHAIN CONFORMATION OF POLYMER MELTS IN CONTRACTION FLOW

A constitutive model of quasi-Newtonian fluid based on the type of flow is used in abrupt planar contraction now.The numerical results from finite element analysis are consistent with experimental data for stress patterns and velocityprofiles in the flow field. The chain conformations of polymer melts are then investigated in such a planar contraction byusing the phenomenological model with internal parameters proposed by the author. That is, the shape and orientation ofpolymer chain coils are predicted and discussed in different flow regions of the contraction flow field that possess simpleshear flow, extensional flow, vortical flow, and mixed flow respectively.

An Improved Markov Chain Model Based on Autocorrelation and Entropy Techniques and Its Application to State Prediction of Water Resources

According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.

Compressed wormlike chain moving out of confined space: A model of DNA ejection from bacteriophage

The molecular biomechanics of DNA ejection from bacteriophage is of interest to not only fundamental biological understandings but also practical applications such as the design of advanced site-specific and controllable drug delivery systems. In this paper, we analyze the viscous motion of a semiflexible polymer chain coming out of a strongly confined space as a model to investigate the effects of various structure confinements and frictional resistances encountered during the DNA ejection process. The theoretically predicted relations between the ejection speed, ejection time, ejection length, and other physical parameters, such as the phage type, total genome length and ionic state of external buffer solutions, show excellent agreement with in vitro experimental observations in the literature.