The article aims to study the effect of layer thickness and reflection coefficient variation on the image of synthetic seismogram, which is generated by using Ricker Wavelet with wide range of frequencies (20-130Hz) and Vibrator Sweeps with many freq
uencies ranges (5-170Hz) as a known technique in reflection seismic method on land. The Researcher tried to
determine the relationship between signals recording times and reflection coefficients variation from first side, and recording times with layer thickness variation from second side. The result which is observed that; the recorded times increased proportionally with increasing of the layer thickness (as we
know), but it is delayed with exponential relation when the velocity and density are varied within the same layer. New manner is applied to represent the result by using the conversion of time seismic section to raster images by using GIS,
this way gave us ability to control the colored scale which reflects the amplitude of recorded signals, and follows the reflectors or get important information about signals amplitude even though the layer thickness is decreased less than wavelet length ten times if we used Ricker signal or Vibration Sweeps.
This study aims to design a neural model for a linear or nonlinear systems by using an Evolutionary Programming algorithm (EP) to choose the optimal structural construction for the network. We have used Matlab to design Neural Networks using (EP), be
cause of its flexibility and ability to represent matrices (Cell Arrays, Multi Dimension Arrays). The experimental results confirm the efficiency with which this algorithm (EP) obtains the optimal network. We have tested the algorithm performance and the resulting model robustness by canceling one of the hidden layer nodes of the best net resulting from applying (EP). The effectiveness of that canceling on the resulting model output is also tested, and this study has shown the efficiency of the algorithm (EP) for the class of systems used.
The relation between rainfall and runoff forms one of the main hydrological cycle elements. It is one of the most complex hydrological phenomena because of the great numbers of parameters used in modeling the physical processes, the expansion of thei
r parameter space, and the temporary change in watershed specifications. Thus, modeling the relation between rainfall and runoff is necessary for hydrological and hydraulic engineering design, integrated management of water resourses, and forecasting flood and preventing its dangers. This research aims at modeling the relation between rainfall and runoff in Alkabeer Aljononbee catchment. It depends on the technique of Artificial Neural Network (ANN). The mathematical model was built by the ntstool and nntool available in the Matlab program. This model depends on daily rainfall, evaporation, air temperature, and relative humidity data taken from meteorological stations that are distributed in the watershed. The daily runoff data have also been used for checking the performance accuracy of the network, using the Simulink technique. The results of this research confirm that artificial neural network technology offers good results in modeling the relation rainfall-runoff, depending on the set of data used. So it could be a better alternative than traditional approaches.
Accurately modeling rainfall-runoff (R-R) transform remains a challenging task despite that a wide range of modeling, either knowledge-driven or data-driven. knowledge-driven models need a large amount of parameters, so it suffers from plenty numbers
of parameters, for this reason the hydrologists start looking for a simple modeling methods, that need a few parameters such as data _driven methods, so The present study amis to use artificial neural network, which is one type of this methods for modeling the relationship between rainfall and runoff in Alkabeer Aljanonbee river catchment in Tartous City. Elman Neural Network is depended on for prediction of runoff by testing twenty four models have different architectures. So all models have been tested by using different numbers of neurons in the hidden layer, by using nntool book, which is available in the Matlab program.
The results of the research verify that the model which has each of temperature, relative humidity, evaporation and rainfall in the input layer with time delay equal to three days (0:-3), in addation to preveous value of runoff (-1:-3), gives a best performance for used data with mean square error equal to 2.8*10^-5, and correlation coefficient 0.96. So it has been reached that Elman network technology gives a good results in modeling the relation rainfall_runoff So it could be a good alternative instead of traditional approaches.
Evaporation forms one of the hydrology cycle elements that it's hard to measure its actual amounts in the field conditions, so it’s estimated by calculations of experimental relations, which depend on climatic elements data. So the research goal is t
o build a mathematical model to estimate monthly evaporation amount in plain area of Syrian Coast, using Artificial Neural Network (ANN), and depending on dry air temperature, and produce comparison study between the results of network and other models. The mathematical model was built by the (NN-tool box), which is one of the v tools. A multilayer ANN architecture of error Back-propagation algorithm was built. The suitable training algorithms, number of hidden layers, number of neurons in each hidden layer, were determined.
The results showed that the ANN (1-9-1) was the best model with MSE of 0.0032 for validation group, using Transfer Function Logsigmoid and Linear in hidden and output layers, respectively.
A comparison model for the results obtained from the proposed ANN with EVANOV model by using SIMULINK technique was developed. This indicated that the ANN using temperature only gives results more accurate than EVANOV equation in determining evaporation.
The low cost, ease of deployment has exposed WSNs an attractive choice for numerous applications,like environmental monitoring applications , security applications, real time tracking, and so on.
But in reality, these networks are operated on batte
ry with limitations in their computation capabilities, memory, bandwidth ,so they called networks with resource constrained nature, and this impels various challenges in its design and its performance.
Limited battery capacity of sensor nodes makes energy efficiency a major and challenge problem in wireless sensor networks. Thus, the routing protocols for wireless sensor networks must be energy efficient in order to maximize the network lifetime.
In this paper we simulated LEACH,SEP,DEEC,TEEN routing protocols and evaluated their performance by comparing with DT routing protocol in Homogeneous and Heterogeneous Wireless Sensor Networks on MATLAB.
This search includes studying of automated mobile cranes to reduce incidence of
inversing which often happens due to payload swaying that requires controlling system at
the crane's site to reach Target position and another controlling system to red
uce payload
swaying as possible while the crane is in motion.
Despite the development of controlling systems that adjust the operation and
functions of these cranes, the repetition of accidental tips in these cranes lead us to look for
hybrid fuzzy controlling system comparing it with PID controlling system. So, it will
improve the performance of these cranes through the reduction of payload swaying and
precise control of crane’s position.
The PID controller and Hybrid Fuzzy PID controller were simulated using Matlab
Software and the results were compared to reach the best controlling system for the crane.
Evapotranspiration forms one of the hydrology cycle elements that it's hard to
measure its actual amounts in the field conditions, so it’s estimated by calculations of
experimental relations that depend on climatic elements data. These estimations
include
different errors because of approximation processes. The research goals to accurate
estimation of the monthly reference evapotranspiration amount in Safita area (on the east
coast of the Mediterranean Sea), and the research depends on the technique of Artificial
Neural Network (ANN), and the mathematical model was built by the
(nftool), which is one of the Matlab tools, depending on monthly air temperature and
relative humidity data which were taken from Safita meteorological station, and the data of
monthly pan evaporation (Class A pan) has been used, after modifying its results, for the
purpose of checking the performance accuracy of the network, by using Simulink
technique, which is existing in Matlab Programs Package. The results of the research
verify that a multi-layer ANN of error Back-propagation algorithm gives a good result in
estimating monthly reference Evapo-transpiration for the used data group.
Industrialists interested automates their factories to increase production, reduce costs
and improve quality by using robots in leadership and finishing most of the production
processes, where robots characterized as mechanical structures programma
ble to perform
tasks accurate, speed and reliability.
Research depend in concluding the optimal path on generating virtual paths
(triangular, curved, square) reflects the robotic arm movement to reach the target point,
where as it has been known moving time and angles of rotation and torque in the joints
under the influence of gravity through the study of horizontal and vertical movement of the
robotic arm.
A study of suggested trajectories for the robotic arm shows that the best paths on the
safety of robotic arm motors is semi-circular path as limiting the occurrence of mechanical
shocks or the appearance of high values of the joints torques. while showing that the path
that achieves less time to reach the target point and less amount of energy is the triangular
path in the case of horizontal motion of the robotic arm despite the emergence of sharp
deviations in the torque and power schemas as a result of the sudden change in the
direction of movement.
The negative impact of gravity is especially apparent when the second joint up or
down movement, causing the appearance of peaks in energy curve reflects the high values
of determination in this joint.
في المشكلة التي نعالجها, تحتاج شركة اتصالات إلى بناء مجموعة من الأبراج الخلوية لتوفير خدمة الاتصالات الخليوية للسكان في منطقة جغرافية. تم تحديد عدد من المواقع المحتملة لبناء الأبراج. يعتم اختيار هذه المواقع على عدة عوامل ، بما في ذلك مدى اتساق البرج
مع البيئة المحيطة وارتفاع التضاريس, تتمتع الأبراج بمدى تغطية ثابت ، وبسبب قيود الميزانية ، لا يمكن بناء سوى عدد محدود منها . بالنظر إلى هذه القيود ، ترغب الشركة في توفير تغطية لأكبر قدر ممكن من السكان, والهدف هو اختيار في أي من المواقع المحتملة يجب أن تقوم الشركة ببناء الأبراج.
إن المشكلة التي شرحناها يمكن نمذجتها لتصبح أحد أمثلة مشكلة 0/1 knapsack الشهيرة لذلك شرحنا في الحلقة مفهوم مشكلة 0/1 Knapsack والطرق المستخدمة في الحل, وتوسعنا في الشرح عن خوارزمية Branch and Bound كونها تعتبر أفضلها.
