Physical Rules Based Adaptive Neuro-Fuzzy Inferential Sensor Model Design and Analysis in Predicting the Indoor Temperature in Heating System

2012 ◽  
Vol 516-517 ◽  
pp. 370-379 ◽  
Author(s):  
Liang Huang ◽  
Zai Yi Liao ◽  
Hua Ge ◽  
Lian Zhao
Keyword(s):  
Energy Efficiency ◽  
Prediction Model ◽  
Performance Measures ◽  
Heating System ◽  
Model Design ◽  
Indoor Temperature ◽  
Sensor Model ◽  
Neuro Fuzzy ◽  
Robust Prediction ◽  
Indoor Comfort

The previous research on adaptive neuro-fuzzy inferential systems (ANFIS) presented an approach to estimating the average indoor temperature in the building environment. However, the restriction on robustness limited the energy efficiency and indoor comfort ratio. An accurate and robust prediction model is proposed in this paper. Comparing to the previous unphysical rules based ANFIS prediction model, the improvement of the physical rules based ANFIS prediction model will be presented and the reason of better performance of this new model will be discussed. Three performance measures are using in evaluating the proposed prediction model.

scholarly journals Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems

2021 ◽  
Author(s):  
Liang Huang
Keyword(s):  
Optimal Control ◽  
Prediction Model ◽  
High Energy ◽  
Space Heating ◽  
Indoor Temperature ◽  
Rule Based ◽  
Heating Systems ◽  
Neuro Fuzzy ◽  
Physical Sensors ◽  
Robust Prediction

The previous research on adaptive neuro-fuzzy inferential sensor (ANFIS) presented an approach to estimate the average indoor temperature and proposed a new method to measure process variables which are impossible to measure directly by using physical sensors in buildings. To achieve high energy efficiency in heating systems, an accurate and robust prediction model is essential. This thesis aims to improve the conventional ANFIS indoor temperature estimator and look for an optimal control of space heating systems. A physical-rule based ANFIS prediction model is proposed. The differences between this physical-rule based ANFIS prediction model and the conventional ANFIS prediction model are presented and analyzed. Three performance measures (RMSE, RMS, and R

Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor vs. GA-BP Based Prediction Model in Indoor Temperature Predicting

2012 ◽  
Vol 594-597 ◽  
pp. 2179-2185
Author(s):  
Liang Huang ◽  
Zai Yi Liao
Keyword(s):  
Prediction Models ◽  
Back Propagation ◽  
District Heating ◽  
Heating System ◽  
Good Prediction ◽  
Indoor Temperature ◽  
District Heating System ◽  
Rule Based ◽  
Neuro Fuzzy ◽  
Indoor Comfort

The previous research on temperature prediction presented different approaches which are physical-rule based adaptive neuro-fuzzy inferential sensor (ANFIS) model and GA-BP (genetic algorithm back propagation) based model to estimate the average indoor temperature in the building environment. Their good prediction performances improved energy efficiency of district heating system and indoor comfort ratio. However, either of these two models has its drawback in a certain condition. In this paper, the two prediction models are reviewed and evaluated by three performance measures (RMSE, RMS, and R2). Their limitations are discussed and potential solution is proposed.

scholarly journals Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor For Optimal Control Of Space Heating Systems

2021 ◽  
Author(s):  
Liang Huang
Keyword(s):  
Optimal Control ◽  
Prediction Model ◽  
High Energy ◽  
Space Heating ◽  
Indoor Temperature ◽  
Rule Based ◽  
Heating Systems ◽  
Neuro Fuzzy ◽  
Physical Sensors ◽  
Robust Prediction

The previous research on adaptive neuro-fuzzy inferential sensor (ANFIS) presented an approach to estimate the average indoor temperature and proposed a new method to measure process variables which are impossible to measure directly by using physical sensors in buildings. To achieve high energy efficiency in heating systems, an accurate and robust prediction model is essential. This thesis aims to improve the conventional ANFIS indoor temperature estimator and look for an optimal control of space heating systems. A physical-rule based ANFIS prediction model is proposed. The differences between this physical-rule based ANFIS prediction model and the conventional ANFIS prediction model are presented and analyzed. Three performance measures (RMSE, RMS, and R

scholarly journals Experimental Investigation and Energy Performance Simulation of Mongolian Ger with ETS Heater and Solar PV in Ulaanbaatar City

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5840
Author(s):  
Bat-Erdene Bayandelger ◽  
Yuzuru Ueda ◽  
Amarbayar Adiyabat
Keyword(s):  
Energy Efficiency ◽  
Heating System ◽  
Energy System ◽  
Energy Performance ◽  
Comfort Level ◽  
Solar Pv ◽  
Pv System ◽  
Performance Simulation ◽  
Central Energy ◽  
Indoor Comfort

There are approximately 200,000 households living in detached houses and gers (yurts) with small coal stoves that burn raw coal in Ulaanbaatar city. A proper heating system and improvement of the energy efficiency of residential dwellings are vitally important for Ulaanbaatar city to reduce air pollution as well as for the operation of the current central energy system. This study shows the experimental results for two gers with two different heating systems and different thermal insulation, for investigating the merits of each. The technical feasibility of the system consisting of an electric thermal storage (ETS) heater with a daytime charging schedule and areal photovoltaic (PV) system was also examined by using a simulation with software developed in MATLAB (R2020a, MathWorks, USA). As a result of the experiment, the indoor comfort level and energy efficiency of the ger with added insulation and an ETS heater with nighttime charging were shown to be enhanced compared with those of the reference ger. The ger with added insulation and the ETS heater consumed 3169 kWh for electric appliances and 5989 kWh for the heating season. The simulation showed that the PV self-consumption rate is 76% for the Ger 2 with the ETS heater because of the daytime charging schedule of the ETS heater. The PV system supplied 31% of the total energy consumed, with the remaining 69% from the main grid.

Analysis of the Heating and Energy Saving Effect of Capillary Radiant Ceiling in Hot Summer and Cold Winter Area

2014 ◽  
Vol 960-961 ◽  
pp. 599-602 ◽  
Author(s):  
Qing Mei Wen ◽  
Dong Yang ◽  
Ming Jiu Chen ◽  
Yong An Li ◽  
Shi Jun Wei
Keyword(s):  
Finite Element ◽  
Energy Saving ◽  
Composite System ◽  
Heating System ◽  
Radiant Heating ◽  
Cold Winter ◽  
Radiation Heating ◽  
Indoor Temperature ◽  
Saving Effect ◽  
Indoor Comfort

This paper introduces the advantages of capillary roof radiant heating system, by using finite element numerical method, the indoor temperature distribution of capillary radiant roof and underfloor supply air composite system is simulated, using the theory of exergy to analysis the energy saving of the system, the result proves that the system can well satisfy indoor comfort requirements, and compared with the floor radiation heating system can saving energy 65.8%, has great research value.

Design of Temperature Measured Terminal with GPRS in the Central Heating Room and Research of the Charging Method by Indoor Temperature Measured

2012 ◽  
Vol 499 ◽  
pp. 445-449
Author(s):  
Wan Jiang Zhang ◽  
Guang Yang ◽  
Ying Zhang ◽  
Kai He
Keyword(s):  
Energy Efficiency ◽  
Heating System ◽  
Building Energy ◽  
New Method ◽  
The Internet ◽  
Building Energy Efficiency ◽  
Heating Period ◽  
Indoor Temperature ◽  
Central Heating ◽  
Heat Metering

The paper explores a new method of the heating measurement and charging in the central heating system. The method is different from mechanical heat metering and ultrasonic heat metering existing now. However, by measuring the indoor temperature and recording the temperature periodically during the heating period, and upload the data which are measured and stored in the terminal periodically to the Internet serve by GPRS. It can adjust the charging according to the actual indoor temperature which is transmitted by the terminal. Finally not only can the system meet the requirements of the users in the heating period, but also achieve the building energy efficiency. Adhere to people-oriented principle. Make the service of heating become more and more humanized.

Stock Market Prediction using Data Mining Techniques

2020 ◽  
pp. 310-313
Author(s):  
Karunesh Makker ◽  
Prince Patel ◽  
Hrishikesh Roy ◽  
Sonali Borse
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Prediction Model ◽  
Efficient Market Hypothesis ◽  
Deterministic System ◽  
Vast Number ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Using Data ◽  
Robust Prediction

Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.

scholarly journals Does Energy Poverty Affect Energy Efficiency Investment Decisions? First Evidence from a Stated Choice Experiment

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1698
Author(s):  
Dimitris Damigos ◽  
Christina Kaliampakou ◽  
Anastasios Balaskas ◽  
Lefkothea Papada
Keyword(s):  
Energy Efficiency ◽  
Choice Experiment ◽  
Alternative Energy ◽  
Investment Decisions ◽  
Heating System ◽  
Energy Poverty ◽  
Protection Measures ◽  
Information Campaigns ◽  
Effective Option ◽  
Vulnerable Households

Energy poverty is a multidimensional and continuously growing societal problem, with political roots. In pursuit of mitigating the problem, the European Commission has adopted a bundle of policies, such as consumer protection measures, short-term financial interventions, motivations for energy efficiency (e.g., energy retrofits and replacement of old household appliance) and information campaigns, among others. There is no doubt, however, that increasing the income of vulnerable households would be the most preferred and effective option. Focusing on energy efficiency, a measure typically incorporated in the National Energy and Climate Plans (NECPs) of many Member States as a means to fight energy poverty, this paper aims to shed light on the need to gradually move towards more localized—not to say personalized—actions. In this direction, a labeled choice-based experiment is used, which involves a hypothetical selection between three alternative energy interventions, i.e., house retrofit, upgrading of heating system and upgrading of household electrical appliances. The research aims to integrate the preferences of households from the choice experiment with indicators of energy poverty and establish a connection between energy poverty and energy efficiency investment decisions. The results demonstrate that households’ preferences are affected by qualitative and quantitative aspects of energy vulnerability and sociodemographic characteristics. Furthermore, vulnerable households seem to be more prone to the so-called “discounting gap”, as previous studies also suggest. These findings are worrisome because, without tailor-made support, these households may never escape the vicious circle of energy poverty. To this end, the survey could provide useful information to policy-makers towards developing more robust policies of energy poverty alleviation.

scholarly journals Indoor Climate Performance in a Renovated School Building

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2827
Author(s):  
Pavla Mocová ◽  
Jitka Mohelníková
Keyword(s):  
Indoor Environment ◽  
Natural Ventilation ◽  
Carbon Dioxide Concentration ◽  
Heating System ◽  
Climatic Conditions ◽  
School Building ◽  
Ventilation Strategy ◽  
Indoor Climate ◽  
Microbiological Testing ◽  
Indoor Comfort

Indoor climate comfort is important for school buildings. Nowadays, this is a topical problem, especially in renovated buildings. Poorly ventilated school classrooms create improper conditions for classrooms. A post-occupancy study was performed in a school building in temperate climatic conditions. The evaluation was based on the results of long-term monitoring of the natural ventilation strategy and measurements of the carbon dioxide concentration in the school classroom’s indoor environment. The monitoring was carried out in an old school building that was constructed in the 1970s and compared to testing carried out in the same school classroom after the building was renovated in 2016. Surprisingly, the renovated classroom had a significantly higher concentration of CO2. It was found that this was due to the regulation of the heating system and the new airtight windows. The occupants of the renovated classroom have a maintained thermal comfort, but natural ventilation is rather neglected. A controlled ventilation strategy and installation of heat recovery units are recommended to solve these problems with the classroom’s indoor environment. Microbiological testing of the surfaces in school classrooms also shows the importance of fresh air and solar radiation access for indoor comfort.

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