scholarly journals An Improved Case-Based Reasoning Model for Simulating Urban Growth

2021 ◽  
Vol 13 (11) ◽  
pp. 6146
Author(s):  
Xin Ye ◽  
Wenhui Yu ◽  
Lina Lv ◽  
Shuying Zang ◽  
Hongwei Ni
Keyword(s):  
Urban Growth ◽  
Urban Areas ◽  
Control Method ◽  
Growth Models ◽  
Case Based Reasoning ◽  
Initial State ◽  
Simulation Accuracy ◽  
Complex Dynamic Systems ◽  
Time Control ◽  
Case Based

Developing urban growth models enables a better understanding and planning of sustainable urban areas. Case-based reasoning (CBR), in which historical experience is used to solve problems, can be applied to the simulation of complex dynamic systems. However, when applying CBR to urban growth simulation, problems such as inaccurate case description, a single retrieval method, and the lack of a time control mechanism limit its application accuracy. In order to tackle these barriers, this study proposes a CBR model for simulating urban growth. This model includes three parts: (1) the case expression mode containing the “initial state-geographical feature-result” is proposed to adapt the case expression to the urban growth process; (2) in order to improve the reliability of the results, we propose a strategy to introduce the “retrieval quantity” parameter and retrieve multiple similar cases; and (3) a time factor control method based on demand constraints is proposed to improve the power of time control in the algorithm. Finally, the city of Jixi was used as the study area for simulation, and when the “retrieval quantity” is 10, the simulation accuracy reaches 97.02%, kappa is 85.51, and figure of merit (FoM) is 0.1699. The results showed that the proposed method could accurately analyze urban growth.

scholarly journals Distributed Finite-Time Bipartite Consensus for Multiagent System with Event-Triggered Control

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Haibo Xie ◽  
Zhengjiang Liu ◽  
Chengyong Yan ◽  
Shibo Zhou
Keyword(s):  
Finite Time ◽  
Control Method ◽  
Initial State ◽  
Consensus Control ◽  
Whole Process ◽  
Time Control ◽  
Consensus Values ◽  
Bipartite Consensus ◽  
Necessary And Sufficient ◽  
Event Triggered

This paper investigates the distributed finite-time event-triggered bipartite consensus control for multiagent systems over antagonistic networks. Under the constraint of energy conservation, a distributed nonlinear finite-time control protocol only depending upon local information is proposed coupled with event-triggered strategies, where controllers of agents at triggered instants are only updated to reduce the computation. It is proved that when the antagonistic network is structurally balanced with a spanning tree, a necessary and sufficient condition is established to guarantee all agents to reach consensus values with identical magnitude but opposite signs. More interestingly, the settling time depending on the initial state is obtained over the whole process. Comparing to asymptotic control algorithms, the proposed control method has better disturbance rejection properties and convergence rate. Simulations are given to demonstrate the effectiveness of the theoretical results.

Temporal Case-Based Reasoning for Personalized Hypertensive Treatment

2016 ◽  
Author(s):  
Niloofar Jalali ◽  
Stephen Agboola ◽  
Kamal Jethwani ◽  
Ibrahim Zeid ◽  
Sagar Kamarthi
Keyword(s):  
Medical Records ◽  
Current Approach ◽  
Treatment Regime ◽  
First Episode ◽  
Case Based Reasoning ◽  
Initial State ◽  
Hypertensive Patients ◽  
The Past ◽  
Clinical Records ◽  
Case Based

Most of the current problems can be solved by referring to the solutions of the previous problems. Case Based reasoning (CBR) is one of the methods that solves a problem by retrieving the similar problems from the past and adapting the solutions of the past problems to solve the new problem. Recent studies that apply CBR include time as a parameter to retrieve most effective solutions that vary with time. This approach is more helpful in healthcare area in which one needs to look at historical evidence to find an accurate diagnostic or treatment regime. Hence, in this study, a time-based CBR is applied to track the outcomes of the drug therapy on hypertensive patients and find the most effective drug as a prescription. Initially, episodes in each patient’s medical records are chronologically ordered such that the oldest episode is placed first in the episode sequence and the latest episode is placed the last. It is assumed that the first episode of each patient is the first instance of diagnose; so when a new patient comes for checkup, his/her state (health condition) is compared with the initial state of the past patients. Therefore, the retrieval process calculates the similarity between the new patient’s current state and the most similar patients at their first episodes in the patient records. Due to the diversity of therapies for matching patients, the best treatment couldn’t be determined without knowing the efficacy of the different treatments. Therefore, the subsequent episodes of matching patients are examined to find the best treatment for the new patient. This might even require using a combination of treatments from all matching patients to find a good treatment for the new patient. After the treatment is defined for the first visit, the record of the new patient is stored in the library for future case retrieval. This method is a novel approach to personalized treatment of patients having chronic disease by tracking the medical records past patients over a long period of time. The current approach for treating the hypertensive patients uses evidence-based guidelines for managing the disease. However, this approach is more general and doesn’t take into account all the patient characteristics such as lab results and physical examination parameters. In the current approach the similarity between patients can’t be leveraged; the change of the treatment regime is based only on the risk parameter. However, in this method several parameters are being checked for efficiency of the medication. In contrast, the proposed CBR-based method personalizes the treatment based on what worked well for similar patients. In this paper, the clinical records of hypertensive patients are provided by a Boston based hospital. The preliminary results confirm that the proposed approach will give good recommendation for hypertension treatment.

Research on the Air-Fuel Ratio Intelligent Control Method for Coke Oven Combustion Energy Saving

2011 ◽  
Vol 121-126 ◽  
pp. 2873-2877 ◽  
Author(s):  
Gong Fa Li ◽  
Yuan He ◽  
Guo Zhang Jiang ◽  
Jian Yi Kong ◽  
Liang Xi Xie
Keyword(s):  
Energy Saving ◽  
Working Conditions ◽  
Gas Flow ◽  
Control Method ◽  
Combustion Process ◽  
Coke Oven ◽  
Case Based Reasoning ◽  
Fuel Ratio ◽  
Intelligent Technology ◽  
Case Based

Coke combustion process, the constant proportion of the combustion air-fuel ratio control results in low combustion efficiency and fault-prone, difficult to adapt to changes in complex working conditions. Application of intelligent technology of case-based reasoning, fuzzy control, proposed for intelligent energy saving air-fuel ratio control method. Based on current trends in working conditions and combustion process in case of failure, predict the typical faults with case-based reasoning technology to the combustion process. On this basis, through case-based reasoning algorithm realize the real-time air-fuel ratio correction. Based on fuzzy-PID temperature cascade control we can obtain the appropriate flue gas flow and flue suction and realize the stability of the combustion process to achieve optimal control.

scholarly journals Comparative Evaluation of Open Source Urban Simulation Models Applied to Colombo City and Environs in Sri Lanka

2021 ◽  
pp. 49-60
Author(s):  
P. Jayasinghe ◽  
L.N. Kantakumar ◽  
V. Raghavan ◽  
G. Yonezawa
Keyword(s):  
Open Source ◽  
Urban Growth ◽  
Urban Areas ◽  
Comparative Evaluation ◽  
Growth Models ◽  
Simulation Models ◽  
Good Choice ◽  
Surface Generation ◽  
Suitable Model ◽  
Urban Simulation

Availability of a variety of urban growth models make model selection to be an important factor in urban simulation studies. In this regard, a comparative evaluation of available urban growth models helps to choose a suitable model for the study area. Thus, we selected three open-source simulation models namely FUTURES, SLEUTH and MOLUSCE to compare in their simplest state to provide a guidance for selection of an urban growth model for Colombo. The urban extent maps of 1997, 2005, 2008, 2014 and 2019 derived from Landsat imageries were used in calibration and validation of models. Models were implemented with the minimum required data with default settings. The simulation results indicate that the estimated quantity of urban growth (148.91 km2) during 2008-2019 by FUTURES model is matching closely with observed urban growth (127.37 km2) during 2008-2019. On the other hand, the SLEUTH model showed an overestimation (250.56 km2) and MOLUSCE showed an underestimation (77.11 km2). Further, the spatial accuracy of urban growth simulation of SLEUTH (Figure of Merit = 0.26) is relatively better in comparison to FUTURES (0.20) and MOLUSCE (0.20). Considering the tradeoff between computational overheads and obtained results, FUTURES could be a good choice over SLEUTH and MOLUSCE, when these models implemented in their simplest form with minimum required datasets. As a future work, we propose the incorporation of exclusion factor for potential surface generation to mitigate the overestimation of urban areas in SLUETH.

scholarly journals Improvement of an Urban Growth Model for Railway-Induced Urban Expansion

2020 ◽  
Vol 12 (17) ◽  
pp. 6801
Author(s):  
Alvin Christopher G. Varquez ◽  
Sifan Dong ◽  
Shinya Hanaoka ◽  
Manabu Kanda
Keyword(s):  
Urban Growth ◽  
Urban Areas ◽  
Historical Data ◽  
Growth Models ◽  
Urban Expansion ◽  
Grid Spacing ◽  
Urban Growth Model ◽  
Sleuth Model ◽  
The Right ◽  
Better Than

Increasing population in urban areas drives urban cover expansion and spatial growth. Developing urban growth models enables better understanding and planning of sustainable urban areas. The SLEUTH model is an urban growth simulation model which uses the concept of cellular automata to predict land cover change using six spatial inputs of historical data (slope, land use, exclusion, urban, transportation, and hill-shade). This study investigates the potential of SLEUTH to capture railway-induced urban growth by testing methods that can consider railways as input to the model, namely (1) combining the exclusion layer with a station map; (2) creating a new input layer representing stations in addition to the default six inputs. Districts in Tsukuba, Japan and Gurugram, India which historically showed evidence of urban growth by railway construction are investigated. Results reveal that both proposed methods can capture railway impact on urban growth, while the former algorithm under the right settings may perform better than the latter at finer resolutions. Coarser resolution representation (300-m grid-spacing) eventually reduces the differences in accuracy among the default SLEUTH model and the proposed algorithms.

Automatic Setting Control of the Raw Slurry Blending Process Based on the Case-Based Reasoning

2011 ◽  
Vol 299-300 ◽  
pp. 667-670 ◽  
Author(s):  
Lun Hai Yin ◽  
Rui Bai ◽  
Wan Li Guo
Keyword(s):  
Control Method ◽  
Raw Materials ◽  
Optimal Operation ◽  
Case Based Reasoning ◽  
Process Data ◽  
Alumina Production ◽  
Control Objective ◽  
Operation Control ◽  
Blending Process ◽  
Case Based

Raw slurry blending process is the key process in the sintering alumina production. In this blending process, raw materials are alkali powder, red mud, blending ore and limestone, and the product is the raw slurry. The optimal operation control objective of this blending process is to make the quality indices of the raw slurry into their targeted ranges. The key step to realize this control objective is to decide the appropriate set-points of the control loop. An automatic setting control method is proposed in this paper. During the setting process, case-based reasoning is adopted to obtain the appropriate set-points of the control loops according to the process data and state. By using this setting control method, appropriate set-points can be obtained and the operation control objectives can be realized.

The Use of Spatial Metrics and Population Data in Mapping the Rural-Urban Transition and Exploring Models of Urban Growth in Hanoi, Vietnam

2021 ◽  
Vol 12 (1) ◽  
pp. 156-168
Author(s):  
Du’o’ng H. Nông ◽  
Jefferson M. Fox ◽  
Sumeet Saksena ◽  
Christopher A. Lepczyk
Keyword(s):  
Urban Growth ◽  
Urban Areas ◽  
Urban Landscape ◽  
Growth Models ◽  
Population Data ◽  
Landscape Fragmentation ◽  
Spatial Metrics ◽  
Transition Zones ◽  
Urban Transition ◽  
Reliable Methods

The process by which cities (or urban areas) expand over time has remained a key focus for geographers, ecologists and other scientists interested in urban phenomena for decades. This study investigated the use of spatial metrics and population data for defining and mapping rural-urban transition zones in Hanoi and exploring urban growth models. The analysis showed that in 2010, about 30% of communes within Hanoi could be defined as rural, 38% as peri-urban and 32% as urban. The peri-urban communes showed a greater level of landscape fragmentation and a higher pace of population growth than rural communes. The urban landscape of Hanoi in 2010 shows characteristics of both transportation corridors and dispersed sites models—the two least eco-friendly models of urbanization. This study provides an effective method for mapping such rural-urban transition and identifies forms of urbanization in places where other socio-economic data sources are limited. This is particularly useful for planners and development agencies that require reliable methods for collecting and analysing data, which can enable them to assess variables along the rural-to-urban continuum.

scholarly journals Integrated Modeling and Intelligent Control Methods of Grinding Process

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Jie-sheng Wang ◽  
Na-na Shen ◽  
Shi-feng Sun
Keyword(s):  
Intelligent Control ◽  
Control Method ◽  
Soft Sensor ◽  
Integrated Modeling ◽  
Case Based Reasoning ◽  
Grinding Process ◽  
Control Methods ◽  
Set Point ◽  
Self Tuning ◽  
Case Based

The grinding process is a typical complex nonlinear multivariable process with strongly coupling and large time delays. Based on the data-driven modeling theory, the integrated modeling and intelligent control method of grinding process is carried out in the paper, which includes the soft-sensor model of economic and technique indexes, the optimized set-point model utilizing case-based reasoning, and the self-tuning PID decoupling controller. For forecasting the key technology indicators (grinding granularity and mill discharge rate of grinding process), an adaptive soft-sensor modeling method based on wavelet neural network optimized by the improved shuffled frog leaping algorithm (ISFLA) is proposed. Then, a set point optimization control strategy of grinding process based on case-based reasoning (CBR) method is adopted to obtain the optimized velocity set-point of ore feed and pump water feed in the grinding process controlled loops. Finally, a self-tuning PID decoupling controller optimized is used to control the grinding process. Simulation results and industrial application experiments clearly show the feasibility and effectiveness of control methods and satisfy the real-time control requirements of the grinding process.

Sign in / Sign up

Export Citation Format

Share Document