Mengjie Han

Mengjie Han
Dalarna University · micro-data analysis

Doctor of Philosophy

About

50
Publications
17,243
Reads
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1,012
Citations
Introduction
Mengjie Han currently works at the micro-data analysis, Dalarna University. Mengjie does research in Social Policy, Qualitative Social Research and Quantitative Social Research.

Publications

Publications (50)
Article
Full-text available
Location Models are used to locate n service centers in order to serve a geographically distributed population. A cornerstone of such models is the measure of distance between the service center and a set of demand points, viz, the location of the population (customers, pupils, patients and so on). Evidence support the current practice of using the...
Article
This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse to what extent local population change is affected by neighbouring populations. To do this, we focused on...
Article
Full-text available
The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances...
Article
Full-text available
Considering the situation where decision values are \(q\)-rung orthopair triangular fuzzy number (\(q\)-ROTFN) and pair-wise comparisons of alternatives and evaluation matrices are given by decision-makers, a new group decision-making method is necessary to be studied for solving a group decision-making problem in the above situation. In this paper...
Article
Full-text available
At the beginning of 2022 the global daily count of new cases of COVID-19 exceeded 3.2 million, a tripling of the historical peak value reported between the initial outbreak of the pandemic and the end of 2021. Aerosol transmission through interpersonal contact is the main cause of the disease’s spread, although control measures have been put in pla...
Article
Household electricity demand has substantial impacts on local grid operation, energy storage and the energy performance of buildings. Hourly demand data at district or urban level helps stakeholders understand the demand patterns from a granular time scale and provides robust evidence in energy management. However, such type of data is often expens...
Preprint
At the beginning of 2022 the global daily count of new cases of COVID-19 exceeded 3.2 million, a tripling of the historical peak value reported between the initial outbreak of the pandemic and the end of 2021. Aerosol transmission through interpersonal contact is the main cause of the disease’s spread, although control measures have been put in pla...
Chapter
Building ventilation system needs to be controlled in a smart way to maintain indoor air quality while reducing energy use. Although many demand-controlled methods have been developed, the design of ventilation schedule has to be customized depending on local climate, occupant behavior and system capacity. This article introduces an easy-to-use con...
Chapter
The Predicted Mean Vote (PMV) model is extensively used by current thermal comfort standards, such as ASHRAE 55 and ISO 7730, despite its discrepancy in predicting Thermal Sensation (TS). The implicit assumption is that PMV can be applied for predicting TS of a large population. Our statistical analysis of a subset of ASHRAE global database of ther...
Chapter
The energy shortage is one key issue for sustainable development, a potential solution of which is the integration with the renewable energy resources. However, the temporal sequential characteristic of renewable resources is different from traditional power grid. For the entire power grid, it is essential to match the energy generation side with t...
Chapter
An occupant’s window opening and closing behaviour can significantly influence the level of comfort in the indoor environment. Such behaviour is, however, complex to predict and control conventionally. This chapter, therefore, proposes a novel reinforcement learning (RL) method for the advanced control of window opening and closing. The RL control...
Chapter
Urban energy mapping plays a crucial role in benchmarking the energy performance of buildings for many stakeholders. This study examined a set of buildings in the city of Borlänge, Sweden, owned by the municipality. The aim was to present a digital spatial mapping of both electricity use and district heating demand. A toolkit for top-down data proc...
Chapter
Full-text available
The lighting system accounts for 8% of the total electricity consumption in commercial buildings in the United States and 12% of the total electricity consumption in public buildings globally. This consumption share can be effectively reduced using the demand-response control. The traditional lighting system control method commonly depends on the r...
Chapter
Classical building control systems are becoming vulnerable with increasing complexities in contemporary built environments and energy systems. Due to this, the reinforcement learning (RL) method is becoming more distinctive and applicable in control networks for buildings. This chapter, therefore, conducts a comprehensive review of RL techniques ap...
Article
Traditional occupant behavior modeling has been studied at the building level, and it has become an important factor in the investigation of building energy consumption. However, studies modeling occupant behaviors at the urban scale are still limited. Recent work has revealed that urban big data can enable occupant behavior modeling at the urban s...
Article
Full-text available
A digital twin is regarded as a potential solution to optimize positive energy districts (PED). This paper presents a compact review about digital twins for PED from aspects of concepts, working principles, tools/platforms, and applications, in order to address the issues of both how a digital PED twin is made and what tools can be used for a digit...
Article
Full-text available
Urban energy mapping plays a crucial role in benchmarking the energy performance of buildings for many stakeholders. This study examined a set of buildings in the city of Borlänge, Sweden, owned by the municipality. The aim was to present a digital spatial map of both electricity use and district heating demand in the spatial-temporal dimension. A...
Article
Full-text available
In recent years, a building's energy performance is becoming uncertain because of factors such as climate change, the Covid-19 pandemic, stochastic occupant behavior and inefficient building control systems. Sufficient measurement data is essential to predict and manage a building's performance levels. Assessing energy performance of buildings at a...
Article
Full-text available
The identification of underground geohazards is always a difficult issue in the field of underground public safety. This study proposes an interactive visualization framework for underground geohazard recognition on urban roads, which constructs a whole recognition workflow by incorporating data collection, preprocessing, modeling, rendering and an...
Article
Full-text available
Multi-label classification (MLC) is a supervised learning problem where an object is naturally associated with multiple concepts because it can be described from various dimensions. How to exploit the resulting label correlations is the key issue in MLC problems. The classifier chain (CC) is a well-known MLC approach that can learn complex coupling...
Article
Full-text available
Occupant behavior in buildings has been considered the major source of uncertainty for assessing energy consumption and building performance. Modeling frameworks are usually built to accomplish a certain task, but the stochasticity of the occupant makes it difficult to apply that experience to a similar but distinct environment. For complex and dyn...
Article
An occupant's window opening and closing behaviour can significantly influence the level of comfort in the indoor environment. Such behaviour is, however, complex to predict and control conventionally. This paper, therefore, proposes a novel reinforcement learning (RL) method for the advanced control of window opening and closing. The RL control ai...
Article
Full-text available
The lighting system accounts for 8% of the total electricity consumption in commercial buildings in the United States and 12% of the total electricity consumption in public buildings globally. This consumption share can be effectively reduced using the demand-response control. The traditional lighting system control method commonly depends on the r...
Article
In the last four decades several methods have been used to model occupants’ presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents...
Article
The Predicted Mean Vote (PMV) model is extensively used by current thermal comfort standards, such as ASHRAE 55 and ISO 7730, despite its discrepancy in predicting Thermal Sensation (TS). The implicit assumption is that PMV can be applied for predicting TS of a large population. Our statistical analysis of a subset of ASHRAE global database of ther...
Article
Full-text available
The energy shortage is one key issue for sustainable development, a potential solution of which is the integration with the renewable energy resources. However, the temporal sequential characteristic of renewable resources is different from traditional power grid. For the entire power grid, it is essential to match the energy generation side with t...
Article
Full-text available
Building control systems are prone to fail in complex and dynamic environments. The reinforcement learning (RL) method is becoming more and more attractive in automatic control. The success of the reinforcement learning method in many artificial intelligence applications has resulted in an open question on how to implement the method in building co...
Article
Full-text available
The solar energy share in Sweden will soar over the next decades. Such transition offers not great opportunity but uncertainties for the emerging solar PV/thermal (PV/T) technologies. There are still critical challenges for PV/T development in Swedish scenario. This paper aims to investigate the local policies and market structures in Sweden by a s...
Article
Classical building control systems are becoming vulnerable with increasing complexities in contemporary built environments and energy systems. Due to this, the reinforcement learning (RL) method is becoming more distinctive and applicable in control networks for buildings. This paper, therefore, conducts a comprehensive review of RL techniques appl...
Article
Full-text available
The aim of this paper is to analyse labour turnover in retail firms with stores in different city locations. This case study of a Swedish mid-sized city uses comprehensive longitudinal register data on individuals. In a first step, an unconditional descriptive analysis shows that labour turnover in retail is higher in out-of-town locations, compare...
Article
Full-text available
The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few...
Article
Full-text available
The emergence of renewable-energy-source (RES) envelope solutions, building retrofit requirements and advanced energy technologies brought about challenges to the existing paradigm of urban energy systems. It is envisioned that the building cluster approach—that can maximize the synergies of RES harvesting, building performance, and distributed ene...
Article
Occupants often perform many types of behavior in buildings to adjust the indoor thermal environment. In these types, opening/closing the windows, often regarded as window-opening behavior, is more commonly observed because of its convenience. It not only improves indoor air quality to satisfy occupants' requirement for indoor thermal comfort but a...
Article
This paper empirically measures the potential spillover effects of big-box retail entry on the productivity of incumbent retailers in the entry regions, and investigates whether the effects differ depending on 1) if the entry is in a rural or urban area, and 2) if the incumbent retailers are within retail industries selling substitute or complement...
Article
A recent surge of interest in building energy consumption has generated a tremendous amount of energy data, which boosts the data-driven algorithms for broad application throughout the building industry. This article reviews the prevailing data-driven approaches used in building energy analysis under different archetypes and granularities, includin...
Article
Full-text available
Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced g...
Technical Report
Full-text available
We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on th...
Conference Paper
The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. The first aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to find an e...
Article
Full-text available
Denna artikel visar på en metod för att undersöka hur optimal befolkningens fysiska tillgänglighet till sjukvården är. Detta är relevant med tanke på den svenska storregionala omdaningen som säkerligen kommer provocera fram omprövningar av sjukhusens framtida placering. Med Dalarna som exempel fann vi att en ökning från dagens två till tre optimalt...
Article
Full-text available
In this article we use a method that is handy when investigating how optimal a population's physical access to hospitals is. In Sweden this is a relevant question since regional restructuring most certainly will affect where the future hospitals will be located. By using the region of Dalarna as an example we find that by increasing the present two...
Technical Report
Full-text available
A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be impl...
Article
Full-text available
The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. Howeve...
Article
Full-text available
The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. Distance measure can vary if the accuracy of the road network varies. The first aim in this study is to analyze how the optimal location solutions vary, using the p-medi...
Article
Full-text available
Location Models are used for planning the location of multiple service centers in order to serve a geographically distributed population. A cornerstone of such models is the measure of distance between the service center and a set of demand points, viz, the location of the population (customers, pupils, patients and so on). Theoretical as well as e...

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Projects

Projects (5)
Project
The aim of this Special Issue is to give an opportunity to scientists investigating building energy modelling and optimization at a large scale to publish their works and make large-scale building energy modelling more accurate and feasible.
Project
In this project, we will use smart digital technologies to collect big data sets of mobility patterns and activities of city inhabitants. These data, along with meteorological data, LiDAR data and other GIS based data, will then be used to construct an urban modelling framework that can be used to assess and visualize energy and power demand and greenhouse gas emissions of the building stock and transports in whole cities. The results from the project include improved knowledge and data as well as demonstrated innovations for use in practical urban planning.
Project
This project aims to estimate: the impact of big-box retailer entry on incumbent retailers productivity, and investigate if the impact is heterogeneous depending on local maket size, type of retail industry, distance to surrounding retailers, and firm size; IKEA entry effects on the average labor productivity in durable goods retailing in the entry regions; and, finally, public opinions regarding IKEA entry.