Impact of Level of Detail and Information Content on Accuracy of Function Structure-Based Market Price Prediction Models

2016 ◽  
Author(s):  
Amaninder Singh Gill ◽  
Joshua D. Summers ◽  
Cameron J. Turner
Keyword(s):  
Prediction Models ◽  
Market Price ◽  
Level Of Detail ◽  
Research Approach ◽  
Function Structure ◽  
Amount Of Information ◽  
Market Values ◽  
Grammar Rules ◽  
Model Set ◽  
Function Structures

This paper explores the amount of information stored in the representational components of a function structure: vocabulary, grammar, and topology. This is done by classifying the previously developed functional composition rules into vocabulary, grammatical, and topological classes and applying them to function structures available in an external design repository. The pruned function structures of electromechanical devices are then evaluated for how accurately market values can be predicted using graph complexity connectivity method. The accuracy is inversely with amount of information and level of detail. Applying the topological rule does not significantly impact the predictive power of the models, while applying the vocabulary rules and the grammar rules reduce the accuracy of the predictions. Finally, the least predictive model set is that which had all rules applied. In this manner, the value of a representation to predict or answer questions is quantified through this research approach.

scholarly journals Comparing function structures and pruned function structures for market price prediction: An approach to benchmarking representation inferencing value

2017 ◽  
Vol 31 (4) ◽  
pp. 550-566 ◽  
Author(s):  
Amaninder Singh Gill ◽  
Joshua D. Summers ◽  
Cameron J. Turner
Keyword(s):  
Predictive Model ◽  
Predictive Power ◽  
Market Price ◽  
Level Of Detail ◽  
Market Values ◽  
Price Prediction ◽  
And Topology ◽  
Grammar Rules ◽  
Model Set ◽  
Function Structures

AbstractBenchmarking function modeling and representation approaches requires a direct comparison, including the inferencing support by the different approaches. To this end, this paper explores the value of a representation by comparing the ability of a representation to support reasoning based on varying amounts of information stored in the representational components of a function structure: vocabulary, grammar, and topology. This is done by classifying the previously developed functional pruning rules into vocabulary, grammatical, and topological classes and applying them to function structures available from an external design repository. The original and pruned function structures of electromechanical devices are then evaluated for how accurately market values can be predicted using the graph complexity connectivity method. The accuracy is found to be inversely related to the amount of information and level of detail. Applying the topological rule does not significantly impact the predictive power of the models, while applying the vocabulary rules and the grammar rules reduces the accuracy of the predictions. Finally, the least predictive model set is that which had all rules applied. In this manner, the value of a representation to predict or answer questions is quantified.

Impact of Chaining Method and Level of Completion on Accuracy of Function Structure-Based Market Price Prediction Models

2019 ◽  
Vol 19 (4) ◽  
Author(s):  
Amaninder Singh Gill ◽  
Joshua D. Summers ◽  
Chiradeep Sen
Keyword(s):  
Prediction Models ◽  
Market Price ◽  
Poor Performance ◽  
Future Research ◽  
Function Structure ◽  
Market Prices ◽  
Accuracy And Precision ◽  
Simulation Based ◽  
Function Models ◽  
Model Completion

AbstractThe goal of this paper is to explore how different modeling approaches for constructing function structure models and different levels of model completion affect the ability to make inferences (reason) on the resulting information within the respective models. Specifically, the function structure models are used to predict market prices of products, predictions that are then compared based on their accuracy and precision. This work is based on previous studies on understanding how function modeling and the use of topological information from design graphs can be used to predict information with historical training. It was found that forward chaining was the least favorable chaining type irrespective of the level of completion, whereas the backward-chaining models performed relatively better across all completion levels. Given the poor performance of the nucleation models at the highest level of completion, future research must be directed toward understanding and employing the methods yielding the most accuracy. Moreover, the results from this simulation-based study can be used to develop modeling guidelines for designers or students, when constructing function models.

Impact of Chaining Method and Level of Completion on Accuracy of Function Structure-Based Market Price Prediction Models

2017 ◽  
Author(s):  
Amaninder Singh Gill ◽  
Joshua D. Summers
Keyword(s):  
Prediction Models ◽  
Market Price ◽  
Function Structure ◽  
Topological Information ◽  
Market Prices ◽  
Forward Chaining ◽  
Price Prediction ◽  
Accuracy And Precision ◽  
Model Completion ◽  
Different Levels

The goal of this paper is to explore how different modeling approaches to construct function structure models and different levels of model completion affect the information contained within the respective models. Specifically, the models are used to predict market prices of products. These predictions are compared based on their accuracy and precision. This work is based on previous studies on understanding how function modeling is done and how topological information from design graphs can be used to predict information with historical training. It was found that forward chaining was the least favorable chaining type irrespective of the level of completion. Backward chaining models work relatively better across all completion percentages, while Nucleation models don’t perform as well for a higher completion percentage. Hence, a greater attention is needed to understand and employ the methods yielding the most accuracy.

scholarly journals Conceptual Design of Electromechanical Actuation Systems for Large-Sized Directional Control Valves

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 133
Author(s):  
Tobias Vonderbank ◽  
Katharina Schmitz
Keyword(s):  
Conceptual Design ◽  
Design Process ◽  
Operating Conditions ◽  
Function Structure ◽  
Advantages And Disadvantages ◽  
Conceptual Designs ◽  
Actuation Systems ◽  
Electromechanical Actuation ◽  
Function Structures ◽  
Valve Actuation

Increasing performance in modern hydraulics is achieved by a close investigation of possible enhancements of its components. Prior research has pointed out that electromechanical actuators can form suitable alternatives to hydraulically piloted control systems. Since the requirements at these actuation systems depend on the operating conditions of the system, each actuator can be optimized to the respective hydraulic system. Considering that many different conceptual designs are suitable, the phase of conceptual design plays a decisive role during the design process. Therefore, this paper focuses on the process of developing new conceptual designs for electromechanical valve actuation systems using the method of function structures. Aiming to identify special design features, which need to be considered during the design process of electromechanical actuation systems, an exemplary actuator was designed based on the derived function structure. To highlight the potential of function structures for the development of new electromechanical valve actuation systems, two principal concepts, which allow the reduction of the necessary forces, have been developed by extending the function structure. These concepts have been experimentally investigated to identify their advantages and disadvantages.

A Statistical Approach to Ranking Similarities of Three Function Structure Groups Using Directed Graphs

2018 ◽  
Author(s):  
Briana M. Lucero ◽  
Matthew J. Adams
Keyword(s):  
Statistical Approach ◽  
Directed Graphs ◽  
Proof Of Concept ◽  
Function Structure ◽  
Fundamental Properties ◽  
Design Engineers ◽  
Functional Representation ◽  
Structure Databases ◽  
Further Development ◽  
Function Structures

Prior efforts in the study of engineering design employed various approaches to decompose product design. Design engineers use functional representation, and more precisely function structures, to define a product’s functionality. However, significant barriers remain to objectively quantifying the similarity between two function structures, even for the same product when developed by multiple designers. For function-structure databases this means that function-structures are implicitly categorized leaving the possibility of incorrect categorization and reducing efficacy of returned analogous correlations. Improvements to efficacy in database organization and queries are possible by objectively quantifying the similarity between function structures. The proposed method exploits fundamental properties of function-structures and design taxonomies. We convert function-structures into directed graphs (digraphs) and equivalent adjacency matrices. The conversion maintains the directed (function → flow → function) progression inherent to function-structures and enables the transformation of the function-structure into a standardized graph. For design taxonomies (e.g. D-APPS), graph nodes represent flows in a consistent (but arbitrary) ordering. By exploiting the directional properties of function-structures and defining the flows as the graphical nodes, the objective and standardized comparison of two function-structures becomes feasible. We statistically quantify the association between digraphs using the Pearson Product Moment Correlation (PPMC) for both within-group and between-group comparisons. The method was tested on three product types (ball thrower, food processor, and an ice cream maker) with function-structures defined by various designers. The method suggested herein is provided as a proof-of-concept with suggested verification and validation approaches for further development.

Identifying Product Portfolio Architecture Modularity Using Function and Variety Heuristics

1999 ◽  
Author(s):  
Erik J. Zamirowski ◽  
Kevin N. Otto
Keyword(s):  
Product Variety ◽  
Product Portfolio ◽  
Functional Constraints ◽  
Function Structure ◽  
Customer Needs ◽  
Product Use ◽  
Individual Product ◽  
Product Function ◽  
Target Values ◽  
Function Structures

Abstract This paper proposes a method for identifying product portfolio architecture alternatives based upon customer needs and product function. Customer needs and uses are interpreted according to the variation in performance target values across the market and within the set of individual customer uses. Product uses are represented by function structures consisting of the functions necessary for achieving the use. These individual product use function structures are combined into a monolithic function structure to represent the entire product portfolio. This monolith is then partitioned according to function and product variety heuristics into function clusters that anticipate product modules. This candidate modularity can then be used to deliver product variety across the product portfolio given functional constraints. A portfolio of xerographic products is used as the working example.

scholarly journals Association between Accounting Numbers and Value of Food and Beverages Firms in Nigeria

2015 ◽  
Vol 7 (12) ◽  
pp. 245
Author(s):  
Nyor Terzungwe ◽  
Nasiru Rabiu
Keyword(s):  
Value Relevance ◽  
Stock Exchange ◽  
Investment Decision ◽  
Market Price ◽  
Accounting Information ◽  
Financial Statements ◽  
Annual Reports ◽  
Market Values ◽  
Food And Beverages ◽  
Accounting Numbers

<p>The degree of statistical relationship between the contents of financial statements and market price of equity is what is termed Value relevance of accounting information. It explains stock market measures using financial information variables and it is a very useful guide to investors in pricing of shares. This study examines the extent of association between accounting information variables of earnings, dividend and book value of equity and market value of listed Food and Beverages firms in Nigeria. Data were collected from the published annual reports of the sampled firms and their market values obtained from the official daily list of the Nigerian Stock Exchange (NSE) over a period of 10 years (2001-2010). Using multivariate regression as technique for data analysis, the study established that accounting information of Food &amp; Beverages companies in Nigeria is value relevant. Accordingly, the study recommends the use of financial statements figures of Food and Beverages firms for investment decision.</p>

A study on the grammatical construction of function structures

2005 ◽  
Vol 19 (3) ◽  
pp. 139-160 ◽  
Author(s):  
PRASANNA SRIDHARAN ◽  
MATTHEW I. CAMPBELL
Keyword(s):  
Automated Reasoning ◽  
Black Box ◽  
Graph Grammar ◽  
Functional Information ◽  
Customer Requirements ◽  
Conceptual Engineering ◽  
Grammatical Construction ◽  
Grammar Rules ◽  
Interactive User ◽  
Function Structures

Function structures are used during conceptual engineering design to transform the customer requirements into specific functional tasks. Although they are usually constructed from a well-understood black-box description of an artifact, there is no clear approach or formal set of rules that guide the creation of function structures. To remedy the unclear formation of such structures and to provide the potential for automated reasoning of such structures, a graph grammar is developed and implemented. The grammar can be used by a designer to explore various solutions to a conceptual design problem. Furthermore, the grammar aids in disseminating engineering functional information and in teaching the function structure concept to untrained engineers. Thirty products are examined as a basis for developing the grammar rules, and the rules are implemented in an interactive user environment. Experiments with student engineers and with the automated creation of function structures validate the effectiveness of the grammar rules.

What does hunting market price reflect? The role of species, landscape and management

2015 ◽  
Vol 42 (3) ◽  
pp. 280 ◽  
Author(s):  
M. Martinez-Jauregui ◽  
A. C. Herruzo ◽  
P. Campos
Keyword(s):  
Market Price ◽  
Hedonic Price ◽  
Age Classes ◽  
Mixed Effect ◽  
Small Game ◽  
Market Values ◽  
Hedonic Price Analysis ◽  
Hunting Bag ◽  
Game Hunting ◽  
Joint Consideration

Context Hunting transactions can be considered a composite good that includes various attributes or characteristics. Obtaining information regarding the utility derived from the different characteristics of the hunter’s bag might help elucidate the purchasing behaviour of hunters. This behaviour is, in turn, an important aspect to be considered by land managers in adaptive hunting management. Aims The present study attempts to identify the values given by hunters to species, landscape and management in the pricing of the hunter’s bag. Our analysis is focused on the hunting bag characteristics and adds to previous research the joint consideration of the amount and quality (sex, age classes and trophy) of various species in the hunter’s bag. Methods We use a dataset of 740 forest hunting estates at Andalucía (1 162 405 ha in the south of Spain) with an important mixed-species bag composition and where 225 game-hunting marketed transactions were declared by the hunting managers, including 13 541 hunting journeys. Hedonic-price analysis and mixed-effect models are used. Key results Our results showed that the composition of the harvested species (quantity and trophy of different species, sex and age classes), the activities related to harvesting and organisation of hunting events and landscape in hunting areas are relevant attributes in big-game market transactions. In small-game market transactions, species and landscape are the primary significant variables found. The latter variable plays a more important role in small game than in big game. Conclusions These findings indicated that hunting market values include, in addition to hunters’ recreational experience, ecological and management aspects with a broader social scope. Implications A further discussion regarding the possible conflict among hunter preferences, long-term game-management decisions and ecological goals is also provided.

scholarly journals Prediction of China’s Housing Price Based on a Novel Grey Seasonal Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Dayin Li ◽  
Lianyi Liu ◽  
Haitao Lv
Keyword(s):  
Real Estate ◽  
Prediction Models ◽  
Housing Prices ◽  
Market Price ◽  
Housing Price ◽  
Real Estate Market ◽  
Accurate Prediction ◽  
Price Changes ◽  
New Information ◽  
Seasonal Model

The fluctuation of real estate prices has an important impact on China's economic development. Accurate prediction of real estate market price changes has become the focus of scholars. The existing prediction methods not only have great limitations on the input variables but also have many deficiencies in the nonlinear prediction. In the process of real estate market price forecasting, the priority of data and the seasonal fluctuation of housing price are important influencing factors, which are not taken into account in the traditional model. In order to overcome these problems, a novel grey seasonal model is proposed to predict housing prices in China. The main method is to introduce seasonal factor decomposition into the new information priority grey prediction model. Two practical examples are used to test the performance of the new information priority grey seasonal model. The results show that compared with the existing prediction models, this method has better applicability and provides more accurate prediction results. Therefore, the proposed model can be a simple and effective tool for housing price prediction. At the same time, according to the prediction results, this paper analyzes the causes of housing price changes and puts forward targeted suggestions.

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