The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
In a recent study, a special type of plane overpartitions known as k-rowed plane overpartitions has been studied. The function denotes the number of plane overpartitions of n with a number of rows at most k. In this paper, we prove two identities modulo 8 and 16 for the plane overpartitions with at most two rows. We completely specify the modulo 8. Our technique is based on expanding each term of the infinite product of the generating function of the modulus 8 and 16 and in which the proofs of the key results are dominated by an intriguing relationship between the overpartitions and the sum of divisors, which reveals a considerable link among these functions modulo powers of 2.
A new family of distribution named Double-Exponential-X family is proposed. The proposed family is generated from the double exponential distribution. The forms of the probability densities and hazard functions of two distinct subfamilies of the proposed family are examined and reported. Generalproperties such as moment, survival, order statistics, probability weighted moments and quartile functions of the models are investigated. A sub family of the developed family of double –Exponential-X family of the distribution known as double-Exponential-Pareto distribution was used to fit a real life data on the use of antiretroviral drugs. Molecular simulation of efficacy of antiretroviral drugs is conducted to evaluate the performance of the
... Show MoreThe research presents a case study of collecting materials and raw materials in a visual space that allows them to form a perception and meanings that inform the recipient by reconstructing them and inserting them into the surface of the artistic work and in such a way that the aesthetic act consists of a variety of media, touches and surfaces. The overlap of races within an environment characterized by unity. That is why the researcher in chapter one presented the problem of research, and the focus was on studying the multiplicity of materials and their aesthetic and functional role in the structure of creative work. The aim of the research is enhanced to identify the aesthetic performance function of the multiplicity of ores in the col
... Show MoreIn this paper, we proposed a new class of weighted Rayleigh distribution based on two parameters, scale and shape parameters which are introduced in Rayleigh distribution. The main properties of this class are investigated and derived.
Background: Ischemic heart disease is a major cause of the diastolic heart failure. Risk of heart failures was increased with microvascular coronary disease, which is characterized by left ventricular stiffness with impaired relaxation and reduced compliance. Aim of this study is to estimate the effect of the severity of myocardium ischemia on the left ventricle ejection fraction and left ventricular volume using SPECT with 99mTc MIBI and to compare the results with the echocardiography. The study included 117 subjects with ischemic heart disease were examined using SPECT and echocardiography techniques. The following
... Show MoreQuality function deployment tool is trying to improve health services through this study that will be applied in health sector environment , and be based on applying quality function deployment tool (QFD) TO preferable evaluation of main patients requirements in order to determine the technical requirements that need most attention across improving and developing health services .
Main requirements are determined to patients lying in the hospital (under research) which is (educational Baghdad \ medicine city office) in Baghdad, and other technical requirements through pers
... Show MoreWater pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale
... Show MoreThe local resolving neighborhood of a pair of vertices for and is if there is a vertex in a connected graph where the distance from to is not equal to the distance from to , or defined by . A local resolving function of is a real valued function such that for and . The local fractional metric dimension of graph denoted by , defined by In this research, the author discusses about the local fractional metric dimension of comb product are two graphs, namely graph and graph , where graph is a connected graphs and graph is a complate graph &
... Show MoreMetaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char
... Show MoreThis 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
... Show More