scholarly journals Application of Data Mining in Traditional Benchmark Evaluation Model for Buildings Energy Consumption

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Donglei Wu ◽  
Minwei Guo
Keyword(s):  
Data Mining ◽  
Energy Consumption ◽  
Evaluation Model ◽  
Energy Performance ◽  
Specific Information ◽  
Data Mining Algorithm ◽  
Apriori Algorithm ◽  
Energy Usage ◽  
Benchmark Assessment ◽  
Grey Correlation Analysis

Since the beginning of data mining technologies, buildings have become not just energy-intensive but also information-centric. Data mining technologies have been widely used to utilize the huge quantities of buildings’ operational data to improve their energy systems. Conventional benchmarking of buildings’ energy performance reflects a variety of parameters, such as the number of inhabitants, the environment, the energy efficiency of equipment utilized, and the adjustment of internal temperature. These various elements are then assigned weights to generate a single general indicator. This study presents a reasonable benchmark assessment methodology of conventional buildings’ energy usage based on a data-mining algorithm for acquiring more specific information, like the energy management efficacy of a building, and aiming at the problem of ineffective use of large amounts of energy consumption in public buildings. A mathematical-statistical approach and a data-mining tool are used to analyse the data. The degree of connection between numerous influencing variables (i.e., characteristic parameters) and building’s energy usage is determined using grey correlation analysis. In this work, we have used an enhanced Apriori algorithm to identify the link between the different forms of systems in the same area. In short, the fundamental idea and process of the Apriori algorithm are presented, and preliminary designs of the preprocessing of experimental data as well as the analysis methods are studied to analyse the outcome of the proposed work.

Application of Data Mining Technology Based on Apriori Algorithm

2014 ◽  
Vol 543-547 ◽  
pp. 2036-2039
Author(s):  
Jian Xing Chen
Keyword(s):  
Data Mining ◽  
Computer Simulation ◽  
Association Rule ◽  
Computer Time ◽  
Data Mining Algorithm ◽  
Apriori Algorithm ◽  
Mining Technology ◽  
Computer Data ◽  
Mining Algorithm ◽  
Step Distance

With the continuous expansion of computer simulation scale, the demand for data mining algorithm is also more and more big. The difficulties in computer data mining technology are focused on algorithm development. Apriori algorithm is a kind of computer data mining algorithm which can greatly improve the computational efficiency. The algorithm uses association rule, which can avoid repeated frequently by layer scanning, reducing the computer time. This paper uses Apriori algorithm to design the data mining parameter optimization model of computer 3D human biology simulation, and applies to improve the step three jump. Through the simulation we found step distance appropriate, it provides technical reference for the application of computer simulation technology in sports.

scholarly journals A Comparative Study: Energy Performance Analysis of Conventional Office Buildings at Lucknow

2020 ◽  
Vol 20 (1) ◽  
pp. 24-34
Author(s):  
Farheen Bano ◽  
Vandana Sehgal
Keyword(s):  
Energy Consumption ◽  
Time Use ◽  
Energy Savings ◽  
Energy Performance ◽  
Building Envelope ◽  
Office Buildings ◽  
Energy Audit ◽  
Energy Usage ◽  
Factors Affecting ◽  
Using Data

In this study, the energy consumption of three government and three private office buildings in Lucknow was investigated, and the energy performance index (EPI) for each building was determined. The main purpose of this research was to assess the energy usage of the buildings and identify factors affecting the energy usage. An analysis was performed using data from an energy audit of government buildings, electricity bills of private office buildings, and an on-site visit to determine building envelope materials and its systems. The annual energy consumption of buildings has been evaluated through EPI. The EPI, measured in kilowatt hour per square meter per year, is annual energy consumption in kilowatt hours divided by the gross floor area of the building in square meters. In this study, the energy benchmark for day-time-use office buildings in composite climate specified by Energy Conservation Building Code (ECBC) has been compared with the energy consumption of the selected buildings. Consequently, it has been found that the average EPI of the selected buildings was close to the national energy benchmark indicated by ECBC. Moreover, factors causing inefficient energy consumption were determined, and solutions for consistent energy savings are suggested for buildings in composite climate.

scholarly journals Occupant behavior: a “new” factor in energy performance of buildings. Methods for its detection in houses and in offices.

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Marilena De Simone ◽  
Gianmarco Fajilla
Keyword(s):  
Energy Consumption ◽  
Energy Performance ◽  
Office Buildings ◽  
Occupant Behavior ◽  
Energy Usage ◽  
Advantages And Disadvantages ◽  
Energy Performance Of Buildings ◽  
And Performance

The role that occupants have on energy consumption and performance of buildings is known, but still requires a great deal of research. In this paper, the most common techniques to detect occupancy and occupant behavior in buildings are categorized with their advantages and disadvantages. Being the buildings characterized by different energy usage, the presentation of the studies that applied surveys and monitoring campaigns is conducted with a differentiation between residential and office buildings.

scholarly journals Research on Personnel Performance Evaluation Model Based on Neural Wireless Network Data Mining Algorithm

2020 ◽  
Author(s):  
Wei Liang ◽  
Tingyi Li
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Evaluation Model ◽  
Multiple Input Multiple Output ◽  
Network Data ◽  
Data Mining Algorithm ◽  
Spatial Network ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Frequency Feature

Abstract In order to effectively evaluate personnel performance, a distributed data mining algorithm for spatial networks based on BP neural wireless network is proposed. In the cloud computing environment, an excavator is used to construct multiple input multiple output spatial network data, analyze the data structure, and perform redundant data compression of massive data through time-frequency feature extraction. Combined with adaptive matching filtering method, the characteristics of the data are matched. The spatial frequency feature extraction method is used to locate the features of the multiple-input multiple-output spatial network data, and the fourth-order cumulant slice is used for reorganization. Data in time series. In order to improve the accuracy of data mining, the BP neural network is used to classify and identify the extracted data features to achieve the optimization of data mining. This algorithm improves the accuracy of personnel performance evaluation, and simultaneously establishes a hierarchical analysis and quantitative evaluation model for the performance of government managers, and adjusts the results of hierarchical statistical analysis on government administrators as needed. The performance evaluation and optimization of government administrators were introduced. The empirical analysis results show that the method has higher accuracy for government managers' performance evaluation, higher efficiency of big data processing and better integration.

scholarly journals Research on human performance evaluation model based on neural network and data mining algorithm

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Wei Liang ◽  
Tingyi Li
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Evaluation Model ◽  
Multiple Input Multiple Output ◽  
Network Data ◽  
Data Mining Algorithm ◽  
Spatial Network ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Frequency Feature

Abstract In order to effectively evaluate personnel performance, a distributed data mining algorithm for spatial networks based on BP neural wireless network is proposed. In the cloud computing environment, an excavator is used to construct multiple input multiple output spatial network data, analyze the data structure, and perform redundant data compression of massive data through time-frequency feature extraction. Combined with the adaptive matching filtering method, the characteristics of the data are matched. The spatial frequency feature extraction method is used to locate the features of the multiple-input multiple-output spatial network data. In order to improve the accuracy of data mining, the BP neural network is used to classify and identify the extracted data features to achieve the optimization of data mining. A wireless sensor network is a wireless network composed of a large number of stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes, and transmits the information of the perceived objects in the geographical area covered by the network and finally puts these The information is sent to the owner of the network. This algorithm improves the accuracy of personnel performance evaluation, simultaneously establishes a hierarchical analysis and quantitative evaluation model for the performance of government managers, and adjusts the results of hierarchical statistical analysis on government administrators as needed. The performance evaluation and optimization of government administrators were introduced. The empirical analysis results show that the method has higher accuracy for government managers’ performance evaluation, higher efficiency of big data processing, and better integration.

scholarly journals Modeling and Simulation of a Building towards Energy Efficiency

2019 ◽  
Vol 8 (10) ◽  
pp. 1063-1073
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Generation ◽  
Energy Performance ◽  
Energy Usage ◽  
Existing Building ◽  
Energy Efficient Buildings ◽  
Roof Area ◽  
Tool Building

Residential buildings are the significant energy consumer of the India which is about 24% of the total energy consumption. Energy efficient buildings are the ideal solution to reduce energy consumption in the building sector. The energy efficient buildings can be achieved by incorporating passive features or renewable energy systems or both. The current work aims to perform a retrofitting analysis of an existing building into an energy efficient building. For performing the energy analysis REVIT 2017 tool is used. Using the REVIT 2017 tool building model is developed, building information are loaded and energy analyses are performed. The building is analyzed as two cases. The first case is to estimate energy performance of the existing building. The second case is to incorporate passive features and renewable energy system to the building and evaluate the energy performance. Existing building Energy Usage Intensity (EUI) was 193 kWh/m2 /year. When passive features (Insulation, additional window glazing and efficient air conditioning systems) alone incorporated to the building the building EUI is reduced to 138 kWh/m2 /year. Along with Passive features Photovoltaic modules with different efficiencies 16%, 18% and 20% are considered for renewable energy generation. The energy generation for the different PV modules for three different roof area (40%, 60% and 70% of total roof area) is evaluated. The energy usage intensity varies from 11.4 from -150 kWh/m2 /year for the combination of different efficiency of PV module and the different % of roof area covered. The negative sign indicates the energy generation after the required energy usage. The payback period for only incorporating passive features is 6.3 years and while incorporating PV system with passive features is 9 years.

Investigation of Thermal and Energy Performance of Green Roofs in Florida Climate

2017 ◽  
Author(s):  
Dhruv Sangal ◽  
Hamidreza Najafi
Keyword(s):  
Mathematical Model ◽  
Energy Consumption ◽  
Energy Savings ◽  
Green Roofs ◽  
Building Energy ◽  
The United States ◽  
Energy Performance ◽  
Environmental Benefits ◽  
Energy Usage ◽  
Heating Load

Buildings are responsible for approximately 40% of energy consumption in the United States. Utilizing efficient methods for reduction in energy consumption by buildings is of great importance. Green roofs have been known as an effective approach to reduce building energy usage (associated with cooling and heating load) as well as providing environmental benefits. In the present paper, a mathematical model is developed in MATLAB considering several aspects of green roofs. The model is validated using available data from previous experimental research studies. A simulation is conducted to assess the performance of green roofs in Melbourne, FL. The study includes calculation of the energy savings associated with using a green roof in summer months and winter months.

Energy Usage Intensity of Bank Building Stock: A Case Study in Pakistan

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Khuram Pervez Amber ◽  
Muhammad Waqar Aslam ◽  
Anila Kousar ◽  
Muhammad Sajid Khan ◽  
Ghulam Qadir Chaudhary ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electricity Consumption ◽  
Energy Performance ◽  
Energy Usage ◽  
Degree Days ◽  
Building Stock ◽  
Cooling Degree Days ◽  
Automatic Teller Machines ◽  
Major Factors

Abstract Energy usage intensity (EUI, kWh/m2/year) of a building category helps energy managers and building owners in evaluating the energy performance of their buildings. Banks are energy-intensive buildings, but there is limited research published in this highly energy-intensive building category. In this paper, the energy consumption of 98 bank buildings located in different cities of the AJK region of Pakistan has been critically analyzed and their EUI value has been established. Data were collected through site visits, interviews, and questionnaires. Electricity consumption of each bank branch was normalized using the cooling degree days method and respective annual normalized EUIs were calculated. It was found through analysis that three major factors that drive electricity consumption in bank buildings in Pakistan are building's area, the number of workstations, and the number of automatic teller machines. The EUI of banks in Pakistan has been found to be 222 kWh/m2/yr, which is comparable with the same of eight other countries.

Research on Performance Detection and Evaluation Platform Based on Data Analyzation

2014 ◽  
Vol 962-965 ◽  
pp. 2801-2808
Author(s):  
Dong Hui Li ◽  
Li Jing Shen ◽  
Xiao Zhi Wu ◽  
Chen Ling Pan ◽  
Guang Xin Zhu ◽  
...  
Keyword(s):  
Data Mining ◽  
Evaluation Model ◽  
Data Mining Algorithm ◽  
Decision Tools ◽  
Mining Algorithm ◽  
Performance Evaluation Model ◽  
Information Detection ◽  
And Performance ◽  
Evaluation Platform ◽  
Very High

It is obliged to do research on performance detection and analyzation technology of information system with deepen development of smart grid to avoid risk and investment. This paper proposed a method of information detection and analyzing based on data mining algorithm and performance evaluation model. It is constructed evaluation platform with related smart decision tools which provided by method mention above. Finally, it is proved that the platform has a very high practical value and promotion prospects.

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