Path planning in an unknown environment based on deep reinforcement learning with prior knowledge
Path planning in an unknown environment is a basic task for mobile robots to complete tasks. As a typical deep reinforcement learning, deep Q-network (DQN) algorithm has gained wide popularity in path planning tasks due to its self-learning and ...
Polynomial approximation to manifold learning
Manifold learning plays an important role in nonlinear dimensionality reduction. But many manifold learning algorithms cannot offer an explicit expression for dealing with the problem of out-of-sample (or new data). In recent, many improved algorithms ...
A text-based multi-span network for reading comprehension
Text-based reading comprehension models have great research significance and market value and are one of the main directions of natural language processing. Reading comprehension models of single-span answers have recently attracted more attention and ...
Research on automobile insurance fraud identification based on fuzzy association rules
With the development of automobile insurance industry, how to identify automobile insurance fraud from massive data becomes particularly important. The purpose of this paper is to improve automobile insurance fraud management and explore the application ...
Progress of graph model for conflict resolution in conflict analysis: A systematic review and bibliometrics research
Conflict is an inevitable social phenomenon and the analysis of it can effectively resolve disputes, improve the position of decision makers (DMs), forecast compromise solutions as well. At present, the Graph Model for Conflict Resolution (GMCR), a ...
Multi-criteria decision making and pattern recognition based on similarity measures for Fermatean fuzzy sets
Higher-order fuzzy decision-making methods have become powerful tools to support decision-makers in solving their problems effectively by reflecting uncertainty in calculations better than crisp sets in the last 3 decades. Fermatean fuzzy set proposed by ...
General models for topology layout of oil and gas star-tree pipeline network
Oil&gas gathering pipeline network structure is a significant part of oil&gas field construction, and the rational construction of pipeline network is directly related to the efficiency and benefits of oil&gas field production. Therefore, optimizing the ...
Robust voice user interface for internet-of-things
Internet of things (IoT) plays significant role in the fourth industrial revolution and attracts an increasing interest due to the rapid development of smart devices. IoT comprises factors of twofold. Firstly, a set of things (i.e., appliances, devices, ...
Interpretations of belief functions in approximation operators by covering
The rough set theory and the evidence theory are two important methods used to deal with uncertainty. The relationships between the rough set theory and the evidence theory have been discussed. In covering rough set theory, several pairs of covering ...
Towards optimal ATM cash replenishment using time series analysis
Automatic Teller Machine (ATM) are still largely used to dispense cash to the customers. ATM cash replenishment is a process of refilling ATM machine with a specific amount of cash. Due to vacillating users demands and seasonal patterns, it is a very ...
Continuous marketing in the social business platform based on identifying consumer boring products
In the social business platform, continuous marketing to consumers can fully explore the consumer purchasing potential. However, since consumers can be influenced by their social friends, their tastes often change, which resulting in the cold start ...
Cloud e-mail security: An accurate e-mail spam classification based on enhanced binary differential evolution (BDE) algorithm
The evolution of technology has brought new challenges and opportunities for the different dimensions of feature space. The higher dimension of the feature space is one of the most critical issues in e-mail classification problems due to accuracy ...
Interval fuzzy probability method for power transformer multiple fault diagnosis
Accurately diagnosing power transformer faults is critical to improving the operational reliability of power systems. Although some researchers have made great efforts to improve the accuracy of transformer fault diagnosis, accurate diagnosis of multiple ...
Combination of improved Harris’s hawk optimization with fuzzy to improve clustering in wireless sensor network
A Wireless Sensor Network (WSN) is divided into groups of sensor nodes for efficient transmission of data from the point of measuring to sink. By performing clustering, the network remains energy-efficient and stable. An intelligent mechanism is needed to ...
A Machine learning-based prediction model for the heart diseases from chance factors through two-variable decision tree classifier
This paper addressed the prediction of heart sicknesses from hazard elements through a decision-making tree. We introduced the facts mining technique in public fitness to extract high-degree knowledge from raw data, which facilitates predicting heart ...
Thermal error analysis of tauren EDM machine tool based on FCM fuzzy clustering and RBF neural network
A method that combines temperature field detection, adaptive FCM (Fuzzy c-means) clustering algorithm and RBF (Radial basis function network) neural network model is proposed. This method is used to analyze the thermal error of the spindle reference point ...
Wireless monitoring algorithm of intelligent greenhouse based on fuzzy control
The existing greenhouse monitoring algorithm has a long delay time, so it is unable to carry out effective remote greenhouse monitoring, therefore, a new wireless monitoring algorithm based on the fuzzy control technolog was put forward, which was able to ...
A method of constructing fuzzy implications from the FIφ-construction
In the recent years, several new construction methods of fuzzy implications have been proposed. However, these construction methods actually care about that the new implication could preserve more properties. In this paper, we introduce a new method for ...
A novel fusion model based on deep information mining for wireless propagation modeling
The wireless propagation model is important for accurate 5 G network deployment. However, the traditional wireless propagation model is faced with the problems of limited application scenarios, unstable prediction results and high marginal cost of ...
A new approach to solve fully intuitionistic fuzzy linear programming problem with unrestricted decision variables
In many real-world problems, one may encounter uncertainty in the input data. The fuzzy set theory fits well to handle such situations. However, it is not always possible to determine with full satisfaction the membership and non-membership degrees ...
An intelligent wireless communication model based on multi-feature fusion and quantile regression neural network
Throughout the wireless communication network planning process, efficient signal reception power estimation is of great significance for accurate 5 G network deployment. The wireless propagation model predicts the radio wave propagation characteristics ...
Hybrid spectrum management using integrated fuzzy and femtocells in cognitive domain
In Today’s pandemic situation, ‘Spectrum accessing and smart usage’ is the sacred Mantra uttered by every individual citizen in the world. Work from home for techies, online classes for students, games for kids, webinar for teaching fraternity etc., are ...
Minimal solutions of fuzzy relation inequalities with addition-min composition1
This paper investigates minimal solutions of fuzzy relation inequalities with addition-min composition. It first shows the conditions that an element is a minimal solution of the inequalities, and presents the conditions that the inequalities have a ...
Pseudo-siamese networks with lexicon for Chinese short text matching
Short text matching is one of the fundamental technologies in natural language processing. In previous studies, most of the text matching networks are initially designed for English text. The common approach to applying them to Chinese is segmenting each ...
Multi-armed bandits for bid shading in first-price real-time bidding auctions
Online advertisements are bought through a mechanism called real-time bidding (RTB). In RTB, the ads are auctioned in real-time on every webpage load. The ad auctions can be of two types: second-price or first-price auctions. In second-price auctions, ...
An Intelligent cognitive sensing and detection strategy for medical telemetry networks
In medical telemetry networks, cognitive radio technology is mostly used to avoid licensed spectrum underutilization and by providing access to unlicensed spectrum users without causing interference to primary users, this concept is widely used in ...
Forecasting carbon emissions using a multi-variable GM (1,N) model based on linear time-varying parameters
Faced with serious growing global warming problem, it is important to predict carbon emissions. As there are a lot of factors affecting carbon emissions, a novel multi-variable grey model (GM(1,N) model) based on linear time-varying parameters discrete ...
A novel weighted fuzzy c-means based on feature weight learning
In feature weighted fuzzy c-means algorithms, there exist two challenges when the feature weighting techniques are used to improve their performances. On one hand, if the values of feature weights are learnt in advance, and then fixed in the process of ...
Research on low-quality waste heat recovery system based on fuzzy proportion integration differentiation control
In the current industrial production process, waste heat of low quality is seriously wasted. In order to effectively recover low-quality waste heat, the research group developed a small energy conversion device –Roots power machine. On this basis, the ...
Path planning of spot welding robot based on multi-objective grey wolf algorithm
The path planning of traditional spot welding mostly uses manual teaching method. Here, a new model of path planning is established from two aspects of welding length and welding time. Then a multi-objective grey wolf optimization algorithm with density ...
