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Showing 8 results for Rajabi

G. Azari Takami, R. Rajabi Nezhad,
Volume 6, Issue 4 (winter 2003)
Abstract

Fecundity of Shah-Koolee in the Sefidrood river, which is one of the economic and popular fishes in northern part of Iran, was studied. From April to August 2000, 539 Shah-Koolee fishes were caught at the specific station in the Sefidrood river from the sea shore to Kisum. Seventy one samples of unspawned fishes were taken, the primary biometry was performed, specimens of the different parts of the ovary were prepared and absolute fecundity was determined through gravimetry. Maximum and minimum fecundity rates were 18860 and 2929 eggs, respectively, that related to eight- and three- years old fishes. Relative fecundity was 132±37 and 72 eggs per gram of weight. The relationship between absolute fecundity and length and weight was linear, correlation and numerical quantities of a, b and r were calculated and regression graph was drawn. Gonado Somatic Index (G.S.I.) was used to determine the natural spawning region and calssification was done on the basis of two factors, age and station. It was found that three- years old fishes with a regeneration power of 17.05 in comparison with other age groups had higher potential. This index also showed that Astaneh and Kisum stations were favorable places for natural spawning of these fishes.
A. Masoumi, A. Hemmat, M. Rajabi,
Volume 12, Issue 44 (summer 2008)
Abstract

Due to yield increase, some farmers in Iran plant sugarbeet in 50-cm row spacing instead of conventional 60-cm row spacing. Low row spacings force farmers to harvest three consecutive rows instead of two alternate rows. This would increase the amount of draft requirement to pull the lifter through the soil. In order to use common medium tractors for pulling the three-unit sugarbeet lifter and properly lifting the sugarbeet tubers out of the soil, applying vibration to the shanks of the lifter was taken into considertion. In this study, the effects of vibration frequency and share rake angle of a vibratory lifter on its performance were investigated. Draft, slippage, percentage of broken and non-harvested tubers were determined for four vibration frequencies (0, 9, 10 and 12 Hz) and three share approach angles (11, 24 and 36 deg.), using a factorial experiment arrangement in a randomized complete block design with three replications. The results showed that the variations in draft and slip with frequency and rake angle were similar. Although the minimum value of draft resistance was obtained at 24 deg. of share rake angle with non-vibrated shanks, 50 percent of tubers remained in the soil and were not harvested. However, the non-harvested tubers reduced to only 20 percent when vibration was applied to the lifter. So using the vibrating shanks improved the removal of the tubers out of the soil. A ratio (K) of draft to the harvested tubers (whole and broken tubers) was defined for selecting the optimum combination of the rake angle and vibration frequency. The K ratio was calculated and analyzed for different combinations of the rake angle and vibration frequency. K ratio comparison showed that, for minimizing percentages of broken and non-harvested tubers, the sugarbeet lifter should have share rake angle of 24 deg. and vibrate with frequency of 9 Hz.
R Rajabi-Kanafgourabi, R Ebadi, M Fazilati, S.z Mirhoseini,
Volume 13, Issue 47 (4-2009)
Abstract

The effect of mulberry leaves enrichment with riboflavin in 7, 37, 77 and 127ppm concentrations on larval growth and cocoon characteristics of Bombyx mori L., hybrid 103×104 was studied. Silkworm larvae were fed on fresh mulberry leaves of shin inche nevise enriched with riboflavin once a day. All biological and economical parameters were determined by using standard techniques in sericulture. The results showed that larval weight was greater in 77ppm among treatments on the 7th day of the fifth instar which had 47% increase compared to control. Maximum amount of female cocoon weight and female pupal weight were recorded 1.622g and 1.169g, respectively, in 127ppm while male cocoon weight and pupal weight were greater in 37ppm and recorded to be 1.169g and 0.895g, respectively. Maximum amount of cocoon shell weight and cocoon shell ratio were recorded in 77ppm for male (0.311g and 26.06%) and female (0.318g and 21.46%). Maximum weight of 50 eggs (0.027g) was recorded in 127ppm while high fertility and hatchability was recorded in 77ppm concentration. Effective rate of rearing was maximum in control treatment (72%) with no significant difference compared with other treatments. The overall results showed that riboflavin can be used at 77ppm concentration for the significant increase of cocoon weight, cocoon shell ratio and egg production of silkworm, Bombyx mori L.
A. Mohammadi, M. H. Biglouei, M. R. Khaledian, A. R. Moridnejad, J. Rajabi,
Volume 17, Issue 66 (winter 2014)
Abstract

To study the effects of irrigation durations and land slopes on wetting pattern dimensions, some experiments were performed using an emitter with constant discharge of 4 liters per hour by 2, 4, and 6 hours irrigation durations. Experiments were conducted on lands with the slopes of 0, 5, 15 an 25 percent, with silty loam soil texture in 3 replications in Fathali region, Mogan plain, Iran. Results showed that increasing the land slope caused an increment in wetting pattern dimensions and bulk, in constant irrigation durations. When slope increased, the depth of infiltrated water along the emitter had a little decrease which wasn’t significant. The upstream and downstream components of wetting pattern were symmetrical on 0 percent slope but not on steep lands. So, optimizing the water use, which is saved in the soil, depends on the land slope and the crop should be planted 10 to 25 centimeters away from the dripper. The investigation of soil moisture distribution on wetting pattern in slope lands showed that contrary to the flat lands the main part of the moisture is accumulated in lower part of the emitter, and wetting pattern in these sloping lands was larger than in flat lands.
D. Rajabi, H. Karami, Kh. Hosseini, S. F. Mousavi , S. A. Hashemi,
Volume 19, Issue 73 (fall 2015)
Abstract

Non-linear Muskingum model is an efficient method for flood routing. However, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed in this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used to find an available criterion to verify ICA. In this regard, ICA was applied for Wilson flood routing then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood, the target function was considered as the sum of squared deviation (SSQ) of observed and calculated dischargem. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance however, ICA was in the first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be recommended as an appropriate method to evaluate the parameters of Muskingum non-linear model.


E. Yarmohammadi, S. Shabanlou, A. Rajabi,
Volume 25, Issue 1 (Spring 2021)
Abstract

Optimization of artificial intelligence (AI) models is a significant issue because it enhances the performance and flexibility of the numerical models. In this study, scour depth around bridge abutments with different shapes was estimated by means of ANFIS and ANFIS-Genetic Algorithm. In other words, the membership functions of the ANFIS model were optimized using the genetic algorithm, finding that the performance of ANFIS model was increased. Firstly, effective input parameters on the scour depth around bridge abutments were defined. Then, by using the input parameters, eleven ANFIS and ANFIS-GA models were produced. Next, the superior ANFIS and ANFIS-GA models were introduced by analyzing the numerical results. For example, the correlation coefficient and scatter index for ANFIS model were calculated to be 0.979 and 0.070; for ANFIS-GA, these were 0.986 and 0.056, respectively. In addition, the average discrepancy ratio (DRave) for ANFIS and ANFIS-GA models was 0.984 and 0.988, respectively. Also, it was shown that the ANFIS-GA models had more accuracy, as compared to the ANFIS models. Moreover, a sensitivity analysis showed that Froude number (Fr) and ratio of flow depth to radius of scour hole (h/L) were the most influential input parameters for simulating the scour depth around bridge abutments.

F. Hayati, A. Rajabi, M. Izadbakhsh, . S. Shabanlou,
Volume 25, Issue 1 (Spring 2021)
Abstract

Due to drought and climate change, estimation and prediction of rainfall is quite important in various areas all over the world. In this study, a novel artificial intelligence (AI) technique (WGEP) was developed to model long-term rainfall (67 years period) in Anzali city for the first time. This model was combined using Wavelet Transform (WT) and Gene Expression Programming (GEP) model. Firstly, the most optimized member of wavelet families was chosen. Then, by analyzing the numerical models, the most accurate linking function and fitness function were selected for the GEP model. Next, using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and different lags, 15 WGEP models were introduced. The GEP models were trained, tested and validated in 37, 20- and 10-years periods, respectively. Also, using sensitivity analysis, the superior model and the most effective lags for estimating long-term rainfall were identified. The superior model estimated the target function with high accuracy. For instance, correlation coefficient and scatter index for this model were 0.946 and 0.310, respectively. Additionally, lags 1, 2, 4 and 12 were proposed as the most effective lags for simulating rainfall using hybrid model. Furthermore, results of the superior hybrid model were compared with GEP model that the hybrid model had more accuracy.

A.h. Azimi, S Shabanlou, F. Yosefvand, A. Rajabi, B. Yaghoubi,
Volume 25, Issue 4 (Winiter 2022)
Abstract

In this research, the scour hole depth at the downstream of cross-vane structures with different shapes (i.e., J, I, U, and W) was simulated utilizing a modern artificial intelligence method entitled "Outlier Robust Extreme Learning Machine (ORELM)". The observational data were divided into two groups: training (70%) and test (30%). Then, using the input parameters including the ratio of the structure length to the channel width (b/B), the densimetric Froude number (Fd), the ratio of the difference between the downstream and upstream depths to the structure height (Δy/hst), and the structure shape factor (φ), eleven different ORELM models were developed for estimating the scour depth. Subsequently, the superior model and also the most effective input parameters were identified through the conduction of uncertainty analysis. The superior model simulated the scour values by the dimensionless parameters b/B, Fd, Δy/hst. For this model, the values of the correlation coefficient (R), the variance accounted for (VAF), and the Nash-Sutcliffe efficiency (NSC) for the superior model in the test mode were obtained 0.956, 91.378, and 0.908, respectively. Also, the dimensionless parameters b/B and Δy/hst were detected as the most effective input parameters. Furthermore, the results of the superior model were compared with the extreme learning machine model and it was concluded that the ORELM model was more accurate. Moreover, an uncertainty analysis exhibited that the ORELM model had an overestimated performance. Besides, a partial derivative sensitivity analysis (PDSA) model was performed for the superior model.


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