scholarly journals Forecast of regional water demand based on NSGAII-FORAGM

2021 ◽  
Author(s):  
Jun Li ◽  
Chunye Liu ◽  
Li Tang
Keyword(s):  
Fractional Order ◽  
Relative Error ◽  
Optimization Model ◽  
Water Demand ◽  
Average Relative Error ◽  
Tertiary Industry ◽  
Wide Range ◽  
Yulin City ◽  
Relative Errors ◽  
Regional Water

Abstract Regional water demand is an important basic data for regional engineering planning, design and management. Making full use of multi-source data and prior knowledge to quickly and economically obtain high-precision regional water demand is of great significance to the optimal allocation of regional water resources. In order to accurately predict the regional water demand, this study took Yulin City as a research area to predict the water demand of the city from 2017 to 2019. Aiming at the oscillating characteristics of the regional water demand sequence and the over-fitting problem of traditional prediction models, this study proposed the non-dominated sorting genetic algorithm II-fractional order reverse accumulative grey model (NSGAII-FORAGM). The regional water demand oscillation sequence was transformed into a monotonically decreasing non-negative sequence. Based on the transformation sequence, an optimization model was constructed according to the two objective functions of ‘maximum (or minimum) order’ and ‘best fit to historical data’, and the NSGAII method were adopted to solve the model. The three model structures of ‘fractional order’, ‘reverse accumulation’ and ‘obtaining order through multi-objective optimization model ‘ were tested based on the water use sequence of the three sectors (industry, tertiary industry and domestic) in Yulin City, and the performance of the method is compared with NSGAII-IORAGM, NSGAII-FOFAGM and SOGA-FORAGM. The results showed that the average relative error of the model established in this study for the simulation of industry, tertiary industry (The tertiary industry is a technical name for the service sector of the economy, which encompasses a wide range of businesses), and domestic was 15.54%, 11.20%, 9.98% respectively. The average relative error of the model established in this study for the prediction of industry, tertiary industry and domestic was 9.46%, 7.9%, 1.8% respectively. For the simulation of water demand sequences in three sections, the simulation average relative errors of the other three models were not absolutely dominant except for the SOGA-FORAGM model. The average relative predicted error by the model in this study was the smallest (The relative errors of the three sequence predictions for industry, tertiary industry and domestic were lower than the relative errors of the optimal results of the comparison model, which were 0.97%, 0.72% and 4.5%, respectively), indicating that the model had certain applicability for the water demand prediction of various sectors (industry, tertiary industry and domestic) in the region compared with other models, and can improve the accuracy of the prediction results.

scholarly journals A new model for accurate estimation of gas content and pressure based on Langmuir adsorption equation in Guizhou, China

2019 ◽  
Vol 37 (3-4) ◽  
pp. 288-311 ◽  
Author(s):  
Qingsong Li ◽  
Enyuan Wang ◽  
Zhengpeng Duan ◽  
Junkui Zhu ◽  
Jiahao Wu
Keyword(s):  
Coal Seam ◽  
Relative Error ◽  
Optimization Model ◽  
Classical Model ◽  
Gas Content ◽  
Average Relative Error ◽  
Pressure Data ◽  
New Model ◽  
Mining Areas ◽  
Relative Errors

In order to obtain the functional relationship of gas content and gas pressure, and to accurately calculate the two values which fitting the characteristics of coal seam, the destruction coefficient (X) and the index (ΔP) of the initial velocity of gas emission are introduced to establish the new model with higher precision based on Langmuir equation and destruction type of coal. The applicability of classic model (W-P model) and new optimization model in Guizhou mining areas are studied through the statistics of basic parameter data from 107 groups of coal-seam gas in eight mining areas. The results show that the gas content calculated by the classical model is lower than the measured value, while the gas pressure value is larger than that. The average relative error of gas content and pressure data reach 23.98% and 97.86%, respectively. The gas content and pressure data calculated by the optimization model are well fitted with the measured value. The fitting degree gradually rises with the increase of the sample size, and the average relative errors are 6.44% and 14.27%, respectively. Compared with the classical model, the average relative errors of gas content and pressure calculated by the optimization model reduce by 17.54% and 83.59%, respectively. The optimization model controls the tendency of calculated value error which significantly rises as the ΔP increases. For the coals with different destruction types, the average relative error of calculated gas content in optimization model ranges from 4.40% to 11.99%. And the average relative error of calculated pressure value ranges from 9.84% to 25.80%, both of them are far superior to that of classical model. The optimization model is more accurate for calculating the gas content and pressure in Guizhou.

scholarly journals Productivity Prediction of Fractured Horizontal Well in Shale Gas Reservoirs with Machine Learning Algorithms

2021 ◽  
Vol 11 (24) ◽  
pp. 12064
Author(s):  
Tianyu Wang ◽  
Qisheng Wang ◽  
Jing Shi ◽  
Wenhong Zhang ◽  
Wenxi Ren ◽  
...  
Keyword(s):  
Neural Network ◽  
Relative Error ◽  
Shale Gas ◽  
Gas Production ◽  
Average Relative Error ◽  
Maximum Relative Error ◽  
Gas Reservoirs ◽  
Lstm Network ◽  
Relative Errors ◽  
Productivity Prediction

Predicting shale gas production under different geological and fracturing conditions in the fractured shale gas reservoirs is the foundation of optimizing the fracturing parameters, which is crucial to effectively exploit shale gas. We present a multi-layer perceptron (MLP) network and a long short-term memory (LSTM) network to predict shale gas production, both of which can quickly and accurately forecast gas production. The prediction performances of the networks are comprehensively evaluated and compared. The results show that the MLP network can predict shale gas production by geological and fracturing reservoir parameters. The average relative error of the MLP neural network is 2.85%, and the maximum relative error is 12.9%, which can meet the demand of engineering shale gas productivity prediction. The LSTM network can predict shale gas production through historical production under the constraints of geological and fracturing reservoir parameters. The average relative error of the LSTM neural network is 0.68%, and the maximum relative error is 3.08%, which can reliably predict shale gas production. There is a slight deviation between the predicted results of the MLP model and the true values in the first 10 days. This is because the daily production decreases rapidly during the early production stage, and the production data change greatly. The largest relative errors of LSTM in this work on the 10th, 100th, and 1000th day are 0.95%, 0.73%, and 1.85%, respectively, which are far lower than the relative errors of the MLP predictions. The research results can provide a fast and effective mean for shale gas productivity prediction.

Application of pyrometer and standard sample to determine surface temperature of studied materials

2019 ◽  
pp. 9-13
Author(s):  
V.Ya. Mendeleyev ◽  
V.A. Petrov ◽  
A.V. Yashin ◽  
A.I. Vangonen ◽  
O.K. Taganov
Keyword(s):  
Composite Material ◽  
Surface Temperature ◽  
Relative Error ◽  
Wavelength Range ◽  
Standard Sample ◽  
A Priori ◽  
Temperature Changes ◽  
Surface Temperatures ◽  
Relative Errors ◽  
Normal Emissivity

Determining the surface temperature of materials with unknown emissivity is studied. A method for determining the surface temperature using a standard sample of average spectral normal emissivity in the wavelength range of 1,65–1,80 μm and an industrially produced Metis M322 pyrometer operating in the same wavelength range. The surface temperature of studied samples of the composite material and platinum was determined experimentally from the temperature of a standard sample located on the studied surfaces. The relative error in determining the surface temperature of the studied materials, introduced by the proposed method, was calculated taking into account the temperatures of the platinum and the composite material, determined from the temperature of the standard sample located on the studied surfaces, and from the temperature of the studied surfaces in the absence of the standard sample. The relative errors thus obtained did not exceed 1,7 % for the composite material and 0,5% for the platinum at surface temperatures of about 973 K. It was also found that: the inaccuracy of a priori data on the emissivity of the standard sample in the range (–0,01; 0,01) relative to the average emissivity increases the relative error in determining the temperature of the composite material by 0,68 %, and the installation of a standard sample on the studied materials leads to temperature changes on the periphery of the surface not exceeding 0,47 % for composite material and 0,05 % for platinum.

Performance of Electronic Structure Methods for the Description of Hückel-Möbius Interconversions in Extended π-Systems

2019 ◽  
Author(s):  
Tatiana Woller ◽  
Ambar Banerjee ◽  
Nitai Sylvetsky ◽  
Xavier Deraet ◽  
Frank De Proft ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Basis Set ◽  
Dft Methods ◽  
Molecular Switching ◽  
Wide Range ◽  
Electronic Structure Methods ◽  
Explicitly Correlated ◽  
Relative Errors ◽  
The Stability ◽  
Basis Set Expansion

<p>Expanded porphyrins provide a versatile route to molecular switching devices due to their ability to shift between several π-conjugation topologies encoding distinct properties. Taking into account its size and huge conformational flexibility, DFT remains the workhorse for modeling such extended macrocycles. Nevertheless, the stability of Hückel and Möbius conformers depends on a complex interplay of different factors, such as hydrogen bonding, p···p stacking, steric effects, ring strain and electron delocalization. As a consequence, the selection of an exchange-correlation functional for describing the energy profile of topological switches is very difficult. For these reasons, we have examined the performance of a variety of wavefunction methods and density functionals for describing the thermochemistry and kinetics of topology interconversions across a wide range of macrocycles. Especially for hexa- and heptaphyrins, the Möbius structures have a pronouncedly stronger degree of static correlation than the Hückel and figure-eight structures, and as a result the relative energies of singly-twisted structures are a challenging test for electronic structure methods. Comparison of limited orbital space full CI calculations with CCSD(T) calculations within the same active spaces shows that post-CCSD(T) correlation contributions to relative energies are very minor. At the same time, relative energies are weakly sensitive to further basis set expansion, as proven by the minor energy differences between MP2/cc-pVDZ and explicitly correlated MP2-F12/cc-pVDZ-F12 calculations. Hence, our CCSD(T) reference values are reasonably well-converged in both 1-particle and n-particle spaces. While conventional MP2 and MP3 yield very poor results, SCS-MP2 and particularly SOS-MP2 and SCS-MP3 agree to better than 1 kcal mol<sup>-1</sup> with the CCSD(T) relative energies. Regarding DFT methods, only M06-2X provides relative errors close to chemical accuracy with a RMSD of 1.2 kcal mol<sup>-1</sup>. While the original DSD-PBEP86 double hybrid performs fairly poorly for these extended p-systems, the errors drop down to 2 kcal mol<sup>-1</sup> for the revised revDSD-PBEP86-NL, again showing that same-spin MP2-like correlation has a detrimental impact on performance like the SOS-MP2 results. </p>

scholarly journals A fractional order epidemic model for the simulation of outbreaks of Ebola

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Weiqiu Pan ◽  
Tianzeng Li ◽  
Safdar Ali
Keyword(s):  
Numerical Solution ◽  
Root Mean Square ◽  
Fractional Order ◽  
Relative Error ◽  
Numerical Solutions ◽  
Real Data ◽  
Mean Square ◽  
Order Model ◽  
The Real ◽  
Fractional Orders

AbstractThe Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number $R_{0}$ R 0 , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error $g(U^{*})=0.4146$ g ( U ∗ ) = 0.4146 are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is $g(U^{*})=0.2744$ g ( U ∗ ) = 0.2744 . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data.

Accessibility vs. Feasibility: Optimizing Function Allocation for Accommodation of Heterogeneous Populations

2021 ◽  
pp. 1-36
Author(s):  
Benjamin Knisely ◽  
Monifa Vaughn-Cooke
Keyword(s):  
Optimization Model ◽  
Engineering Students ◽  
Product Variety ◽  
Human Beings ◽  
Heterogeneous Populations ◽  
Trade Offs ◽  
Potential System ◽  
Wide Range ◽  
Need To Evaluate ◽  
Design Case Study

Abstract Human beings are physically and cognitively variable, leading to a wide array of potential system use cases. To design safe and effective systems for highly heterogeneous populations, engineers must cater to this variability to minimize the chance of error and system failure. This can be a challenge because of the increasing costs associated with providing additional product variety. Most guidance for navigating these trade-offs is intended for late-stage design, when significant resources have been expended, thus risking expensive redesign or exclusion of users when new human concerns become apparent. Despite the critical need to evaluate accommodation-cost trade-offs in early stages of design, there is currently a lack of structured guidance. In this work, an approach to function modeling is proposed that allows the simultaneous consideration of human and machine functionality. This modeling approach facilitates the allocation of system functions to humans and machines to be used as an accessible baseline for concept development. Further, a multi-objective optimization model was developed to allocate functions with metrics for accommodation and cost. The model was demonstrated on a design case study. 16 senior mechanical engineering students were recruited and tasked with performing the allocation task manually. The results were compared to the output of the optimization model. Results indicated that participants were unable to produce concepts with the same accommodation-cost efficiency as the optimization model. Further, the optimization model successfully produced a wide range of potential product concepts, demonstrating its utility as a decision-aid.

scholarly journals GIS use in solving water supplying and water environmental problems of Urban Territories

2018 ◽  
Vol 170 ◽  
pp. 04008
Author(s):  
Nadezhda Kurepina ◽  
Irina Rybkina
Keyword(s):  
Water Management ◽  
Research Work ◽  
Environmental Problems ◽  
Geoinformation Systems ◽  
Step Procedure ◽  
Wide Range ◽  
Urban Territories ◽  
Cartographic Modeling ◽  
Academy Of Sciences ◽  
Regional Water

Geoinformation systems (GIS) are actively used in modern scientific research, including the field of Urban Territories’ management. The lack of a universal methodology for their application requires an individual approach in the study of water management and water and environmental problems in the region. The purpose of this article is to demonstrate concrete examples of GIS successful use in solving some water supplying problems. One of the leading research methods is geoinformation-cartographic modeling, which has a wide range of possibilities and contributes to the effective solution of water-related and water-ecological regional problems. The developed algorithm for GIS using in solving regional water, a step-by-step procedure organizes for carrying out research work, the presented structure of the thematic database facilitates the systematizatin of thematic data large volume with the base a GIS project is created, where information is integrated, calculations, and a cartographic model is created that visualizes the regional water management and water-e logical situation. The research examples carried out in the Institute of Hydrometeorology of the Russian Academy of Sciences (Siberian Branch) on regional water management and water ecological problems by means of GIS and using the method of geoinformation-cartographic modeling considered in this paper prove the effectiveness and their use expediency.

scholarly journals Predicting Indoor Temperature Distribution Based on Contribution Ratio of Indoor Climate (CRI) and Mobile Sensors

Buildings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 458
Author(s):  
Yanan Zhao ◽  
Zihan Zang ◽  
Weirong Zhang ◽  
Shen Wei ◽  
Yingli Xuan
Keyword(s):  
Temperature Distribution ◽  
Relative Error ◽  
Prediction Accuracy ◽  
Prediction Method ◽  
Mobile Sensors ◽  
Average Relative Error ◽  
Contribution Ratio ◽  
Mobile Sensor ◽  
Indoor Climate ◽  
Indoor Temperature

In practical building control, quickly obtaining detailed indoor temperature distribution is necessary for providing satisfying personal comfort and improving building energy efficiency. The aim of this study is to propose a fast prediction method for indoor temperature distribution without knowing the thermal boundary conditions in practical applications. In this method, the index of contribution ratio of indoor climate (CRI), which represents the independent contribution of each heat source to the temperature distribution, has been combined with the air temperature collected by one mobile sensor at the height of the working area. Based on a typical office model, the effectiveness of using mobile sensors was discussed, and the influence of its acquisition height and acquisition distance on the prediction accuracy was analyzed as well. The results showed that the proposed prediction method was effective. When the sensors fixed on the wall were used to predict the indoor temperature distribution, the maximum average relative error was 27.7%, whereas when the mobile sensor was used to replace the fixed sensors, the maximum average relative error was 4.8%. This indicates that using mobile sensors with flexible acquisition location can help promote both reliability and accuracy of temperature prediction. In the human activity area, data from a set of mobile sensors were used to predict the temperature distribution at four heights. The prediction accuracy was 2.1%, 2.1%, 2.3%, and 2.7%, respectively. However, the influence of acquisition distance of mobile sensors on prediction accuracy cannot be ignored. The distance should be large enough to disperse the distribution of the acquisition points. Due to the influence of airflow, some distance between the acquisition points and the room boundaries should be given.

A SEM Water Pollutants Emissions Reduction Optimization Model for Pollutant Total Amount Control in a Region

2012 ◽  
Vol 610-613 ◽  
pp. 1579-1582 ◽  
Author(s):  
Jing Ya Wen ◽  
Yan Hu ◽  
Zhao Sun ◽  
Zhuang Li ◽  
Yu Li
Keyword(s):  
Water Pollution ◽  
Optimization Model ◽  
Emission Reduction ◽  
Technical Support ◽  
Emissions Reduction ◽  
Environment Protection ◽  
Validity And Reliability ◽  
Total Amount Control ◽  
Regional Water

On account of severe water pollution condition, this paper combines structure emissions reduction, engineering emissions reduction and management emissions reduction (namely SEM emissions reduction), builds an optimization model for total amount control of regional water pollution, and puts the above model into practice to validate its validity and reliability. According to the case study, the emission reduction of COD and NH3-N are 43.94 and 7.09 (104 tons), respectively. The optimal total costs of reduction is 36.89 (billion yuan), which decreases 7.47% than the existed recommended scheme (39.87 billion yuan). This method can be used for providing technical support and thus achieves the 12th Five-year goals of the environment protection plan more effectively.

scholarly journals Open Quotient Measurements Based on Multiscale Product of Speech Signal Wavelet Transform

2007 ◽  
Vol 2007 ◽  
pp. 1-5 ◽  
Author(s):  
Aïcha Bouzid ◽  
Noureddine Ellouze
Keyword(s):  
Wavelet Transform ◽  
Relative Error ◽  
Speech Processing ◽  
Speech Signal ◽  
Accurate Estimation ◽  
Pitch Period ◽  
Open Time ◽  
Wide Range ◽  
Voiced Speech ◽  
Egg Signal

This paper describes a multiscale product method (MPM) for open quotient measure in voiced speech. The method is based on determining the glottal closing and opening instants. The proposed approach consists of making the products of wavelet transform of speech signal at different scales in order to enhance the edge detection and parameter estimation. We show that the proposed method is effective and robust for detecting speech singularity. Accurate estimation of glottal closing instants (GCIs) and opening instants (GOIs) is important in a wide range of speech processing tasks. In this paper, accurate estimation of GCIs and GOIs is used to measure the local open quotient (Oq) which is the ratio of the open time by the pitch period. Multiscale product operates automatically on speech signal; the reference electroglottogram (EGG) signal is used for performance evaluation. The ratio of good GCI detection is 95.5% and that of GOI is 76%. The pitch period relative error is 2.6% and the open phase relative error is 5.6%. The relative error measured on open quotient reaches 3% for the whole Keele database.

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