This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

The article discusses the spatial analysis of the chemical soil properties that is a key component of the agriculture ecosystem based on satellite images. The main objective of the present study is to measure the chemical soil properties (total dissolved salts (TDS), Electrical conductivity (EC), PH, and) and the ​spatial variability. On 13 November 2020 (wet season), a total of 12 soil samples were collected in the field through random sampling in the Sanam mountain-Al Zubair region south of Basra province, to contain its soil samples components of minerals and precious elements such as silica and sulfur. From experimental results, the soil sample in the sixth position has the highest concentration of TDS values, reached (5798.4

The aim of the research is to determine the impact of profit management practices on the quality of profits through the use of flexibility in determining accounting methods and practices profit information is one of the most important information that concerns current users in general and observing users in particular. Some corporations managements manipulate the results of the company's profit or loss (income statement) and financial position statement with multiple reasons, including capital market motivations to raise their share prices in the stock market and attract investors, and on the other hand the motives of funding and borrowing loans, and the use of the flexibility in accounting policies and estimates to change the in

                The current research aims to show the impact of the international auditing standard IAS 540 in reducing income smoothing practices in Iraq. To achieve the objectives of the research, the researcher adopted a questionnaire for a sample of auditors in Iraq. Where 60 forms were distributed and after the questionnaire was retrieved and statistical analysis was done using the SPSS program, The research reached a number of results, the most important of which are: the existence of a statistically significant effect of the application of the international auditing standard IAS 540 in reducing income smoothing practices, The research recommended the necess

This study has aimed to measure the relationship between the skills required for the labor market and the employment of graduates of community colleges at King Khalid University. For gathering the required data, a questionnaire has been designed and distributed to the faculty members of community colleges at King Khalid University in a random sample method. The chosen sample size has covered (123) individuals. Questionnaire forms have been distributed and retrieved from (117) participants. Therefore, the estimated response has reached 95 % of the total sample size. The results of the study have shown that there is not any significant relationship between the skills which the graduates   acquire and the requirements of employmen