Easy access to time series forecasting provides a strong competitive advantage for any company or organization. As automated forecasting environments become more prevalent in the market, it is crucial to explore their...
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Fasttext is a powerful word representation method that creates word representations based on vectors of character n-grams. In this work, we propose a method that utilizes fasttext features for a novel feature engineer...
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ISBN:
(数字)9798350379433
ISBN:
(纸本)9798350379440
Fasttext is a powerful word representation method that creates word representations based on vectors of character n-grams. In this work, we propose a method that utilizes fasttext features for a novel feature engineering model for the spam detection problem. In the feature engineering method, the combination of average, mean of second derivative; mean peak and standard deviation of fasttext features are computed. Finally, tf-idf features are also considered for the modeling process. The success of each feature engineering technique is measured and reported. The combination of the five feature extraction methods, tested on two spam detection datasets, yielded promising results with an accuracy of 0.978 on e-mail spam detection and an accuracy of 0.986 on sms spam classification.
Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in Io...
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Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.
A continuous dynamic model for the development of a gas field is studied. Two mathematical problems are posed, solved and analyzed. In the direct problem, we are looking for the maximum accumulated profit on a set of ...
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Detailed forecasting of time series is one of the fields where the latest advancements in information technology make significant contributions. Operating with financial data poses noteworthy challenges owing to its i...
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ISBN:
(数字)9798350358100
ISBN:
(纸本)9798350358117
Detailed forecasting of time series is one of the fields where the latest advancements in information technology make significant contributions. Operating with financial data poses noteworthy challenges owing to its inherent nature and substantial impact on economic dynamics within society. This study explores the utilization of automated tools as a set of resources for both unifactorial and multifactorial forecasting, drawing conclusions and providing recommendations.
Static analysis is a method to analyse the source code without executing it. It is widely used to find bugs and code smells in industrial software. Among other methods, the most important techniques are the one based ...
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Function overloading is a well-known technique available in most major programming languages, including $\mathrm{C}^{++}$ , to facilitate compile-time polymorphism. Due to the complex requirements imposed by the $\mat...
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ISBN:
(数字)9798331502232
ISBN:
(纸本)9798331502249
Function overloading is a well-known technique available in most major programming languages, including $\mathrm{C}^{++}$ , to facilitate compile-time polymorphism. Due to the complex requirements imposed by the $\mathbf{C}^{++}$ Language Standard, the behaviour of overload resolution can be surprising even for experienced $\mathbf{C}^{++}$ developers. This is exacerbated by the fact that if an unexpected function is selected in an overloaded situation, most compilers do not explain why. In addition, an overabundance of candidates can be a compilation time bottleneck. Despite its widespread usage, there are not many tools to help programmers analyse overload usage in a software project. We developed an overloading inspector tool, Overlord, based on the open-source LLVM/Clang Compiler Infrastructure. With Overlord developers can list the possible candidate functions for a call site, and obtain step-by-step reasoning about the candidate selection process. Additionally to its comprehension functionality the tool also provides profiling data on overload resolution times to help library authors streamline the set of available overloads for improving the compilation performance.
Nowadays, one of the most demanding areas of Artificial Intelligence application is to forecast the weather condition as rapid and accurate as possible. The ratio of air vapor pressure to saturation vapor pressure is ...
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Interval type-2 fuzzy sets are often used in the designing of fuzzy systems associated with the speed control under uncertainty. In this paper, we consider the possibilities of using interval type-2 fuzzy sets to desc...
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Developing vehicles with the Internet of Thing technology including driver health monitoring systems, driver safety systems, and accident prevention has drawn the attention of researchers in the last few years. The mo...
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