scholarly journals Design and Calibration of Moisture Sensor Based on Electromagnetic Field Measurement for Irrigation Monitoring

Chemosensors ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 251
Author(s):  
Daniel A. Basterrechea ◽  
Javier Rocher ◽  
Mar Parra ◽  
Lorena Parra ◽  
Jose F. Marin ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Absolute Error ◽  
Induced Voltage ◽  
Agricultural Field ◽  
Average Absolute Error ◽  
Moisture Sensor ◽  
Green Areas ◽  
Different Types ◽  
Dry Soil ◽  
Different Characteristics

Soil moisture control is crucial to assess irrigation efficiency in green areas and agriculture. In this paper, we propose the design and calibration of a sensor based on inductive coils and electromagnetic fields. The proposed prototypes should meet a series of requirements such as low power consumption, low relative error, and a high voltage difference between the minimum and maximum moisture. We tested different prototypes based on two copper coils divided into two different sets (P1–P15 and NP1–NP4). The prototypes have different characteristics: variations in the number and distribution of spires, existence or absence of casing, and copper wires with a diameter of 0.4 or 0.6 mm. In the first set of experiments carried out in commercial soil, the results showed that the best prototypes were P5, P8, and P9. These prototypes were used in different types of soils, and P8 was selected for the subsequent tests. We carried the second set of experiments using soil from an agricultural field. Based on the data gathered, mathematical models for the calibration of prototypes were obtained and verified. In some cases, two equations were used for different moisture intervals in a single prototype. According to the verification results, NP2 is the best prototype for monitoring the moisture in agricultural lands. It presented a difference in induced voltage of 1.8 V, at 500 kHz, between wet and dry soil with a maximum voltage of 5.12 V. The verification of the calibration determined that the calibration using two mathematical models offers better results, with an average absolute error of 2.1% of moisture.

scholarly journals General features of Nash equilibria in combinations of elementary interactions in symmetric two-person games

2021 ◽  
Vol 94 (5) ◽  
Author(s):  
György Szabó ◽  
Balázs Király
Keyword(s):  
Mathematical Models ◽  
Nash Equilibria ◽  
Matrix Decomposition ◽  
Payoff Matrix ◽  
Zero Eigenvalue ◽  
Macroscopic Behavior ◽  
Different Types ◽  
Multi Agent ◽  
Different Characteristics ◽  
Pair Interactions

AbstractTwo-person games are used in many multi-agent mathematical models to describe pair interactions. The type (pure or mixed) and the number of Nash equilibria affect fundamentally the macroscopic behavior of these systems. In this paper, the general features of Nash equilibria are investigated systematically within the framework of matrix decomposition for n strategies. This approach distinguishes four types of elementary interactions that each possess fundamentally different characteristics. The possible Nash equilibria are discussed separately for different types of interactions and also for their combinations. A relation is established between the existence of infinitely many mixed Nash equilibria and the zero-eigenvalue eigenvectors of the payoff matrix.

An algebraic approach to N-soft sets with application in decision-making using TOPSIS

2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Real World ◽  
Algebraic Approach ◽  
Multi Criteria Decision Making ◽  
Commutative Monoids ◽  
Soft Sets ◽  
Algebraic Properties ◽  
Different Types ◽  
Selection Of

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.

RELIABILITY ASSESSMENT OF AXIALLY COMPRESSED COMPOSITE CYLINDRICAL SHELLS WITH RANDOM IMPERFECTIONS

2011 ◽  
Vol 11 (02) ◽  
pp. 215-236 ◽  
Author(s):  
MATTEO BROGGI ◽  
ADRIANO CALVI ◽  
GERHART I. SCHUËLLER
Keyword(s):  
Mathematical Models ◽  
Axial Compression ◽  
Cylindrical Shells ◽  
Reliability Assessment ◽  
Buckling Analysis ◽  
Buckling Load ◽  
Experimental Results ◽  
Drastic Decrease ◽  
Different Types ◽  
Probability And Statistics

Cylindrical shells under axial compression are susceptible to buckling and hence require the development of enhanced underlying mathematical models in order to accurately predict the buckling load. Imperfections of the geometry of the cylinders may cause a drastic decrease of the buckling load and give rise to the need of advanced techniques in order to consider these imperfections in a buckling analysis. A deterministic buckling analysis is based on the use of the so-called knockdown factors, which specifies the reduction of the buckling load of the perfect shell in order to account for the inherent uncertainties in the geometry. In this paper, it is shown that these knockdown factors are overly conservative and that the fields of probability and statistics provide a mathematical vehicle for realistically modeling the imperfections. Furthermore, the influence of different types of imperfection on the buckling load are examined and validated with experimental results.

scholarly journals Hidden Semi-Markov Models for Predictive Maintenance

2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Francesco Cartella ◽  
Jan Lemeire ◽  
Luca Dimiccoli ◽  
Hichem Sahli
Keyword(s):  
Markov Models ◽  
Real Data ◽  
Information Criterion ◽  
Absolute Error ◽  
Predictive Maintenance ◽  
Average Absolute Error ◽  
Current State ◽  
Automatic Model Selection ◽  
State Duration ◽  
Useful Lifetime

Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs) with (i) no constraints on the state duration density function and (ii) being applied to continuous or discrete observation. To deal with such a type of HSMM, we also propose modifications to the learning, inference, and prediction algorithms. Finally, automatic model selection has been made possible using the Akaike Information Criterion. This paper describes the theoretical formalization of the model as well as several experiments performed on simulated and real data with the aim of methodology validation. In all performed experiments, the model is able to correctly estimate the current state and to effectively predict the time to a predefined event with a low overall average absolute error. As a consequence, its applicability to real world settings can be beneficial, especially where in real time the Remaining Useful Lifetime (RUL) of the machine is calculated.

scholarly journals Study of a Privacy Preserving Logistic Regression Algorithm (PPLRA) For Data Privacy in the Context of Big Data

2021 ◽  
Vol 2083 (3) ◽  
pp. 032059
Author(s):  
Qiang Chen ◽  
Meiling Deng
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Privacy Protection ◽  
Data Privacy ◽  
Absolute Error ◽  
Average Absolute Error ◽  
Regression Algorithms ◽  
Hadoop Platform ◽  
Logistic Regression Algorithm ◽  
Computing Speed

Abstract Regression algorithms are commonly used in machine learning. Based on encryption and privacy protection methods, the current key hot technology regression algorithm and the same encryption technology are studied. This paper proposes a PPLAR based algorithm. The correlation between data items is obtained by logistic regression formula. The algorithm is distributed and parallelized on Hadoop platform to improve the computing speed of the cluster while ensuring the average absolute error of the algorithm.

scholarly journals Short-Term Traffic Flow Forecasting Model Based on GA-TCN

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Rongji Zhang ◽  
Feng Sun ◽  
Ziwen Song ◽  
Xiaolin Wang ◽  
Yingcui Du ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Convolutional Neural Network ◽  
Traffic Flow ◽  
Absolute Error ◽  
Forecasting Model ◽  
Average Absolute Error ◽  
Short Term ◽  
Traffic Flow Forecasting ◽  
Fitness Value

Traffic flow forecasting is the key to an intelligent transportation system (ITS). Currently, the short-term traffic flow forecasting methods based on deep learning need to be further improved in terms of accuracy and computational efficiency. Therefore, a short-term traffic flow forecasting model GA-TCN based on genetic algorithm (GA) optimized time convolutional neural network (TCN) is proposed in this paper. The prediction error was considered as the fitness value and the genetic algorithm was used to optimize the filters, kernel size, batch size, and dilations hyperparameters of the temporal convolutional neural network to determine the optimal fitness prediction model. Finally, the model was tested using the public dataset PEMS. The results showed that the average absolute error of the proposed GA-TCN decreased by 34.09%, 22.42%, and 26.33% compared with LSTM, GRU, and TCN in working days, while the average absolute error of the GA-TCN decreased by 24.42%, 2.33%, and 3.92% in weekend days, respectively. The results indicate that the model proposed in this paper has a better adaptability and higher prediction accuracy in short-term traffic flow forecasting compared with the existing models. The proposed model can provide important support for the formulation of a dynamic traffic control scheme.

Design and Simulation of Portable Data Terminal for Agriculture Equipment

2013 ◽  
Vol 336-338 ◽  
pp. 383-387
Author(s):  
Yan Xin Yin ◽  
Yu Tan ◽  
Shu Mao Wang
Keyword(s):  
Communication Protocol ◽  
Absolute Error ◽  
Wireless Sensor ◽  
Error Measurement ◽  
Average Absolute Error ◽  
Wireless Communication Protocol ◽  
Data Acquisition Software ◽  
Terminal Design ◽  
Data Terminal ◽  
Reliability And Availability

A portable data terminal design based on wireless sensor network was came up for agriculture equipment working status monitor, a JN5139 module was used as the hardware core of the terminal and Zigbee as the wireless communication protocol. Effect caused by time-delay and pocket loss was simulated and analyzed with Truetime1.5 under matlab, data acquisition software was developed according to the simulation that effectively reduced the influence. Error measurement test showed the analog average absolute error was 6.33mv and frequency average absolute error was 0.56Hz, that indicated the reliability and availability in agriculture application.

scholarly journals Floral Consumption Values for Consumer Groups with Different Purchase Choices for Flowers

2009 ◽  
Vol 19 (3) ◽  
pp. 563-571 ◽  
Author(s):  
Li-Chun Huang ◽  
Tzu-Fang Yeh
Keyword(s):  
Information Search ◽  
Choice Behavior ◽  
Social Value ◽  
Evaluative Judgments ◽  
Consumption Values ◽  
The Social ◽  
Different Types ◽  
Commercial Communication ◽  
Different Characteristics ◽  
The Relationship

Consumption values are theoretically believed to be the antecedents of the outcomes of consumer purchase choice. In the floral market, even though the context of floral consumption values has been explored, the relationship between floral consumption values and consumer's purchase choice regarding floral products remains unknown. This study, however, seeks to address this deficiency by attempting to evaluate the differences in floral consumption values across consumer groups that have different purchase choices for floral products. After collecting data from a consumer survey, which yielded 615 valid questionnaires, the statistical results indicated that consumers who revealed different purchase choices in regard to flowers had different floral consumption values. In descending order, showing care to others, emotion conditioning, and sensory hedonics were the floral consumption values most strongly recognized by the majority of the consumers. However, heavy users of flowers revealed different characteristics in that they more strongly recognized the psychological value of emotion conditioning rather than the social value of showing care to others. The main difference across consumer groups that had purchased flowers with different frequencies or that preferred to buy different types of flowers had to do with the epistemic value (i.e., curiosity fulfillment). The results of this study imply that consumers who have different choice behavior toward flowers possess different evaluative judgments in regard to floral products. Such differences not only lead consumers to have different purchase choices in regard to flowers, but are also very likely to influence the consumer's behavior in regard to information search and variety seeking in the floral market, which in turn, impacts the effectiveness of commercial communication in the floral market.

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