This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-factor model. The results show that the dragonfly algorithm, particularly when using MPT and APT, demonstrates superior performance in improving the accuracy of Fama-MacBeth estimates and enhancing the effectiveness of the KWR approach.
Stone Matrix Asphalt (SMA) is a gap-graded asphalt concrete hot blend combining high-quality coarse aggregate with a rich asphalt cement content. This blend generates a stable paving combination with a powerful stone-on-stone skeleton that offers excellent durability and routing strength. The objectives of this work are: Studying the durability performance of stone matrix asphalt (SMA) mixture in terms of moisture damage and temperature susceptibility and Discovering the effect of stabilized additive (Fly Ash ) on the performance of stone matrix asphalt (SMA) mixture. In this investigation, the durability of stone matrix asphalt concrete was assessed in terms of temperature susceptibility, resistance to moisture damage, and sensitivity t
... Show MoreSustainable development is longer that meet the needs of the present generation without compromising the ability of future generations to meet their own needs as it seeks to harmonize economic, social, Why research aims to check the availability of a proposed program takes into account the evidence and scrutiny of financial commitment and performance audit in accordance with the dimensions of sustainable development (economic, environmental, social and institutional) to measure the extent of the province on the needs of current and future generations, The problem with research that there is no audit program ensures the audit of financial statements, commitment and performance of health services in order to achieve sustainable development
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
In the past two decades, maritime transport traffic has increased, especially in the case of container flow. The BAP (Berth Allocation Problem) (BAP) is a main problem to optimize the port terminals. The current manuscript explains the DBAP problems in a typical arrangement that varies from the conventional separate design station, where each berth can simultaneously accommodate several ships when their entire length is less or equal to length. Be a pier, serve. This problem was then solved by crossing the Red Colobuses Monkey Optimization (RCM) with the Genetic Algorithm (GA). In conclusion, the comparison and the computational experiments are approached to demonstrate the effectiveness of the proposed method contrasted with other
... Show MoreOptimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal threshol
Eleven species of parasitic insects were recovered from puparia of house fly Musca domestica L. developing in animal dung in Baghdad during 1985-1987. Of the parasites obtained, representatives were found in five families of Hymenoptera and one family of Coleoptera. The most prevalent parasites were Spalangia cameroni Perkins, S. nigroaenea Curtis and S. endius Walk. Average parasitism for the two year was 11.30 %, the highest number of parasitism occurred in May and October.
A revised checklist of the robber fly genera (Diptera, Asilidae) was given during this study in Iraq. The investigation showed (21) genera belonging to seven subfamilies, two genera new recorded to entomofauna of Iraq (Promachus Loew, 1848 and Genus: Dysmacus Loew, 1860). Eight genera showed in this investigation and eleven genera were recorded previously to Iraq.
In this paper we use the Markov Switching model to investigate the link between the level of Iraqi inflation and its uncertainty; forth period 1980-2010 we measure inflation uncertainty as the variance of unanticipated inflation. The results ensure there are a negative effect of inflation level on inflation uncertainty and all so there are a positive effect of inflation uncertainty on inflation level.  
... Show MoreIn this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho
... Show MoreIn this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending