scholarly journals Occupant Decision Making In Office Building Fire Emergencies: Experimental Results

1997 ◽  
Vol 5 ◽  
pp. 771-782 ◽  
Author(s):  
Wendy Saunders
Keyword(s):  
Decision Making ◽  
Experimental Results ◽  
Office Building ◽  
Building Fire

scholarly journals A Methodological Framework for Sustainable Office Building Renovation Using Green Building Rating Systems and Cost-Benefit Analysis

2020 ◽  
Vol 12 (15) ◽  
pp. 6156
Author(s):  
Nataša Šuman ◽  
Mojca Marinič ◽  
Milan Kuhta
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Cost Benefit Analysis ◽  
Early Stage ◽  
Cost Benefit ◽  
Green Building ◽  
Office Buildings ◽  
Office Building ◽  
Rating System ◽  
Benefit Analysis

Sustainable development is a priority for the future of our society. Sustainable development is of particular importance to the Architecture, Engineering, and Construction (AEC) industry, both for new buildings and for the renovation of existing buildings. Great potential for sustainable development lies in the renovation of existing office buildings. This paper introduces a new framework for identifying the best set of renovation strategies for existing office buildings. The framework applies selected green building rating system criteria and cost-effective sustainable renovation solutions based on cost-benefit analysis (CBA), and thus provides a novelty in decision-making support for the sustainable renovation of office buildings at an early-stage. The framework covers all necessary steps and activities including data collection, determination of the required level of renovation, selection of the green building rating system, identification of impact categories and criteria, and final evaluation and decision-making using CBA. The framework can be used in conjunction with different systems and according to different regional characteristics. The applicability of the addressing procedure is shown through a case study of a comprehensive renovation of an office building in the city of Maribor.

scholarly journals A Heterogeneous Graph Enhanced LSTM Network for Hog Price Prediction Using Online Discussion

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 359
Author(s):  
Kai Ye ◽  
Yangheran Piao ◽  
Kun Zhao ◽  
Xiaohui Cui
Keyword(s):  
Decision Making ◽  
Essential Role ◽  
Online Discussion ◽  
Professional Community ◽  
Experimental Results ◽  
Agricultural Products ◽  
Price Prediction ◽  
Price Data ◽  
Rich Information ◽  
Lstm Network

Forecasting the prices of hogs has always been a popular field of research. Such information has played an essential role in decision-making for farmers, consumers, corporations, and governments. It is hard to predict hog prices because too many factors can influence them. Some of the factors are easy to quantify, but some are not. Capturing the characteristics behind the price data is also tricky considering their non-linear and non-stationary nature. To address these difficulties, we propose Heterogeneous Graph-enhanced LSTM (HGLTSM), which is a method that predicts weekly hog price. In this paper, we first extract the historical prices of necessary agricultural products in recent years. Then, we utilize discussions from the online professional community to build heterogeneous graphs. These graphs have rich information of both discussions and the engaged users. Finally, we construct HGLSTM to make the prediction. The experimental results demonstrate that forum discussions are beneficial to hog price prediction. Moreover, our method exhibits a better performance than existing methods.

Review Summary Generation in Online Systems: Frameworks for Supervised and Unsupervised Scenarios

2021 ◽  
Vol 15 (3) ◽  
pp. 1-33
Author(s):  
Wenjun Jiang ◽  
Jing Chen ◽  
Xiaofei Ding ◽  
Jie Wu ◽  
Jiawei He ◽  
...  
Keyword(s):  
Decision Making ◽  
Real World ◽  
Text Summarization ◽  
Experimental Results ◽  
Product Review ◽  
Comprehensive Review ◽  
Online Systems ◽  
Real World Datasets ◽  
Different Characteristics

In online systems, including e-commerce platforms, many users resort to the reviews or comments generated by previous consumers for decision making, while their time is limited to deal with many reviews. Therefore, a review summary, which contains all important features in user-generated reviews, is expected. In this article, we study “how to generate a comprehensive review summary from a large number of user-generated reviews.” This can be implemented by text summarization, which mainly has two types of extractive and abstractive approaches. Both of these approaches can deal with both supervised and unsupervised scenarios, but the former may generate redundant and incoherent summaries, while the latter can avoid redundancy but usually can only deal with short sequences. Moreover, both approaches may neglect the sentiment information. To address the above issues, we propose comprehensive Review Summary Generation frameworks to deal with the supervised and unsupervised scenarios. We design two different preprocess models of re-ranking and selecting to identify the important sentences while keeping users’ sentiment in the original reviews. These sentences can be further used to generate review summaries with text summarization methods. Experimental results in seven real-world datasets (Idebate, Rotten Tomatoes Amazon, Yelp, and three unlabelled product review datasets in Amazon) demonstrate that our work performs well in review summary generation. Moreover, the re-ranking and selecting models show different characteristics.

Estimated path information gain-based robot exploration under perceptual uncertainty

Robotica ◽  
2022 ◽  
pp. 1-17
Author(s):  
Jie Liu ◽  
Chaoqun Wang ◽  
Wenzheng Chi ◽  
Guodong Chen ◽  
Lining Sun
Keyword(s):  
Decision Making ◽  
Topological Structure ◽  
Information Gain ◽  
State Of The Art ◽  
Selection Process ◽  
Random Trees ◽  
Experimental Results ◽  
Restricted Area ◽  
Structure Information ◽  
Path Information

Abstract At present, the frontier-based exploration has been one of the mainstream methods in autonomous robot exploration. Among the frontier-based algorithms, the method of searching frontiers based on rapidly exploring random trees consumes less computing resources with higher efficiency and performs well in full-perceptual scenarios. However, in the partially perceptual cases, namely when the environmental structure is beyond the perception range of robot sensors, the robot often lingers in a restricted area, and the exploration efficiency is reduced. In this article, we propose a decision-making method for robot exploration by integrating the estimated path information gain and the frontier information. The proposed method includes the topological structure information of the environment on the path to the candidate frontier in the frontier selection process, guiding the robot to select a frontier with rich environmental information to reduce perceptual uncertainty. Experiments are carried out in different environments with the state-of-the-art RRT-exploration method as a reference. Experimental results show that with the proposed strategy, the efficiency of robot exploration has been improved obviously.

scholarly journals SentiProdBR: Building Domain-Specific Sentiment Lexicons for the Portuguese Language

2021 ◽  
Author(s):  
Tiago de Melo
Keyword(s):  
Decision Making ◽  
Sentiment Analysis ◽  
Online Reviews ◽  
Bayes Theorem ◽  
Experimental Results ◽  
Product Categories ◽  
Domain Specific ◽  
Alternative Approaches ◽  
The Web

Online reviews are readily available on the Web and widely used for decision-making. However, only a few studies on Portuguese sentiment analysis are reported due to the lack of resources including domain-specific sentiment lexical collections. In this paper, we present an effective methodology using probabilities of the Bayes’ Theorem for building a set of lexicons, called SentiProdBR, for 10 different product categories for the Portuguese language. Experimental results indicate that our methodology significantly outperforms several alternative approaches of building domain-specific sentiment lexicons.

scholarly journals Developing a Building Fire Information Management System Based on 3D Object Visualization

2020 ◽  
Vol 10 (3) ◽  
pp. 772 ◽  
Author(s):  
Jung ◽  
Cha ◽  
Jiang
Keyword(s):  
Decision Making ◽  
Information Management ◽  
Management System ◽  
Relevant Information ◽  
Information Management System ◽  
Information Modeling ◽  
Prototype System ◽  
Building Fire ◽  
Emergency Responders ◽  
Fire Information

In a building fire disaster, a variety of information on hazardous factors is crucial for emergency responders, facility managers, and rescue teams. Inadequate information management limits the accuracy and speed of fire rescue activities. Furthermore, a poor decision-making process, which is solely dependent on the experiences of emergency responders, negatively affects the fire response activities. Building information modeling (BIM) enables the sharing of locations of critical elements and key information necessary for effective decision-making on disaster prevention. However, it is non-trivial to integrate and link the relevant information generated during the life cycle of the building. In particular, the information requirements for building fires should be retrieved in the BIM software because most of them have spatial characteristics. This paper proposes a prototype system for a building’s fire information management using three-dimensional (3D) visualization by deriving the relevant information required for mitigating building fire disasters. The proposed system (i.e., Building Fire Information Management System (BFIMS)) automatically provides reliable fire-related information through a computerized and systematic approach in conjunction with a BIM tool. It enables emergency responders to intuitively identify the location data of indoor facilities with its pertinent information based on 3D objects. Through scenario-based applications, the system has effectively demonstrated that it has contributed to an improvement of rapid access to relevant information.

Virtual reality-based decision support model for interior design and decoration of an office building

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Kai Juan ◽  
Hao-Yun Chi ◽  
Hsing-Hung Chen
Keyword(s):  
Decision Making ◽  
Virtual Reality ◽  
Decision Support ◽  
Decision Support System ◽  
Interior Design ◽  
Support System ◽  
Decision Makers ◽  
Office Building ◽  
Design Decision ◽  
Content Type

Purpose The purpose of this paper is to develop a virtual reality (VR)-based and user-oriented decision support system for interior design and decoration. The four-phase decision-making process of the system is verified through a case study of an office building. Design/methodology/approach Different “spatial layouts” are presented by VR for users to decide their preference (Phase 1). According to the selected spatial layout, a “spatial scene” is constructed by VR and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to determine the spatial scene preference (Phase 2). Based on the binary integer programming method, the system provides the optimal preliminary solution under a limited decoration budget (Phase 3). Finally, the consistency between the overall color scheme and pattern is fine-tuned by VR in order to obtain the final solution (Phase 4). Findings The questionnaire survey results show that decision makers generally affirm the operation and application of VR, and especially recognize the advantages in the improvement of VR-based interior design feasibility, communication efficiency and design decision-making speed. The optimization of the costs and benefits enables decision makers to effectively evaluate the impact of design decisions on subsequent project implementation during the preliminary design process. Originality/value The VR-based decision support system for interior design retains the original immersive experience of VR, and offers a systematic multiple criteria decision- making and operations research optimization method, thus, providing more complete decision-making assistance. Compared with traditional design communication, it can significantly reduce cognitive differences and improve decision-making quality and speed.

scholarly journals Using building adaptation to deliver sustainability in Australia

2009 ◽  
Vol 27 (1) ◽  
pp. 46-61 ◽  
Author(s):  
Sara J. Wilkinson ◽  
Kimberley James ◽  
Richard Reed
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Office Building ◽  
Building Stock ◽  
Policy Makers ◽  
Content Type ◽  
Carbon Neutrality ◽  
Building Adaptation ◽  
The Impact ◽  
Decision Making Tool

PurposeThis paper seeks to establish the rationale for existing office building adaptation within Melbourne, Australia, as the city strives to become carbon neutral by 2020. The problems faced by policy makers to determine which buildings have the optimum adaptation potential are to be identified and discussed.Design/methodology/approachThis research adopts the approach of creating a database of all the buildings in the Melbourne CBD including details of physical, social, economic and technological attributes. This approach will determine whether relationships exist between attributes and the frequency of building adaptation or whether triggers to adaptation can be determined.FindingsThis research provided evidence that a much faster rate of office building adaptation is necessary to meet the targets already set for carbon neutrality. The findings demonstrate that a retrospective comprehensive examination of previous adaptation in the CBD is a unique and original approach to determining the building characteristics associated with adaptation and whether triggers can be identified based on previous practices. The implication is that a decision‐making tool should be developed to allow policy makers to target sectors of the office building stock to deliver carbon neutrality within the 2020 timeframe.Practical implicationsDrastic reductions in greenhouse gas emissions are required to mitigate global warming and climate change and all stakeholders should be looking at ways of reducing emissions from existing stock.Originality/valueThis paper adds to the existing body of knowledge by raising awareness of the way in which the adaptation of large amounts of existing stock can be fast tracked to mitigate the impact of climate change and warming associated with the built environment, and in addition it establishes a framework for a decision‐making tool for policy makers.

scholarly journals Parameter Reductions of Bipolar Fuzzy Soft Sets with Their Decision-Making Algorithms

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 949 ◽  
Author(s):  
Ghous Ali ◽  
Muhammad Akram ◽  
Ali N. A. Koam ◽  
José Carlos R. Alcantud
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Theoretical Approach ◽  
Experimental Results ◽  
Soft Sets ◽  
Parameter Reduction ◽  
Reduction Techniques ◽  
Making Choices ◽  
Exact Degree ◽  
Fuzzy Soft Sets

Parameter reduction is a very important technique in many fields, including pattern recognition. Many reduction techniques have been reported for fuzzy soft sets to solve decision-making problems. However, there is almost no attention to the parameter reduction of bipolar fuzzy soft sets, which take advantage of the fact that membership and non-membership degrees play a symmetric role. This methodology is of great importance in many decision-making situations. In this paper, we provide a novel theoretical approach to solve decision-making problems based on bipolar fuzzy soft sets and study four types of parameter reductions of such sets. Parameter reduction algorithms are developed and illustrated through examples. The experimental results prove that our proposed parameter reduction techniques delete the irrelevant parameters while keeping definite decision-making choices unchanged. Moreover, the reduction algorithms are compared regarding the degree of ease of computing reduction, applicability, exact degree of reduction, applied situation, and multi-use of parameter reduction. Finally, a real application is developed to describe the validity of our proposed reduction algorithms.

Modeling of situation assessment in regional air defense combat

2018 ◽  
Vol 16 (2) ◽  
pp. 91-101
Author(s):  
Hai-yan Yang ◽  
Shuai-wen Zhang ◽  
Xu-yu Li
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Bayesian Network ◽  
Particle Swarm ◽  
Flight Path ◽  
Experimental Results ◽  
Situation Assessment ◽  
Swarm Optimization ◽  
Air Defense ◽  
New Framework

The purpose of situation assessment in regional air defense combat is to quickly fuse data as well as to provide commanders with timely support for decision making. We propose a new framework for situation assessment in regional air defense combat, which plays a very concrete role in real combat and follows the combat process. The proposed framework involves three aspects: assessment of the air defense capability of a region; the prediction of an enemy’s invasion route; and the generation of an interception plan. A Bayesian network is used to evaluate and infer the air defense capability of a region. In the network, the calculation of input evidence is based on threat models from radar, the terrain, and anti-aircraft firepower. The weak areas for air defense can be observed when the evaluation is completed. Accordingly, the possible flight path of an enemy invader can be predicted via particle swarm optimization. We build an interception model based on existing attack modes for intercepting enemy aircraft to provide pre-planning for interception. The experimental results prove the feasibility and effectiveness of the proposed method. In particular, the proposed method can contribute to quick decision making in regional air defense combat.

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