Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

The focus of this paper is the presentation of a new type of mapping called projection Jungck zn- Suzuki generalized and also defining new algorithms of various types (one-step and two-step algorithms) (projection Jungck-normal N algorithm, projection Jungck-Picard algorithm, projection Jungck-Krasnoselskii algorithm, and projection Jungck-Thianwan algorithm). The convergence of these algorithms has been studied, and it was discovered that they all converge to a fixed point. Furthermore, using the previous three conditions for the lemma, we demonstrated that the difference between any two sequences is zero. These algorithms' stability was demonstrated using projection Jungck Suzuki generalized mapping. In contrast, the rate of convergenc

The advancements in horizontal drilling combined with hydraulic fracturing have been historically proven as the most viable technologies in the exploitation of unconventional resources (e.g., shale and tight gas reservoirs). However, the number of fractures, well timing, and arrangement pattern can have a significant impact on the project economy. Therefore, such design and operating parameters need to be efficiently optimized for obtaining the best production performance from unconventional gas reservoirs. In this study, the process of selecting the optimal number of fractures was conducted on a section of a tight gas reservoir model (based on data from the Whicher Range (WR) tight gas field in Western Australia). Then, the optimal number

        Throughput accounting is concerned with a throughput measurement process to determine the efficiency of the company, to know the problems and obstacles it suffers from, to determine their causes and ways to address them.The research problem is represented by the following question: does the application of a throughput accounting lead to maximizing the company's profits? The aim of the research is to demonstrate the importance of throughput accounting, which is one of the tools of management accounting in providing an efficient information system that provides the company’s management with the information it needs to improve its production processes, increase a throughput, and thus maxi

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance