I hope everyone's healthy and happy and enjoying the sun. (if in the Southern Hemisphere)
Would somebody mind having a quick check over so the below to know if I'm applying the correct methodology for required application
The Question;
I've decried to put all our garden sprinkler settings into excel to help calculate usage, costs while trying to optimise watering settings.
The general formula I am using is; (I've included a image for an example)
Cost=(R/1000)*L
L=(Flow*T)*Nodes
T=Min*D
D=ROUNDDOWN((End-Start+1)/Interval,0)
Where;
R = Cost Per 1KL
L = Total Litres Used
T = Total Run Time Cost per
1 Kilolitres= 2.99
Flow = 1.6 (Flow Rate Per/Min of 1x 90° Sprinkler Head)
Nodes = Amount of Sprinkler Heads
Min = Watering Run Time in Minutes
Start = Watering Start Date
End = Watering End Date
Interval = Watering Interval Day
Thats the method of calculating the costs. I'd love to hear anyone's thoughts and please do let me know if I've missed anything.
Any feedback would be greatly appreciated and many thanks in advance. :)
P.S; if anyone knows how to calculate the usage and costs for running drip line irrigation, I'd love to hear it. :) (The Drip line is about 153 meters in length with hole spacing every 300mm apart. It's 2.2 l/hr Flow. I haven't been able to think of how to calculate this)
For costing example; (sorry for the image, I didn't know if I could upload a sheet)
OP
https://www.mrexcel.com/board/threads/equation-formula-review-proof-for-garden-watering.1193183/
Related
Calculate project work risk completion rate (in excel) based on
Deadline
Work effort/work-effort weight
of tasks completed
Given
Project Unit: Milestone-1 - Milestone-4, MVP-1 (includes All milestones)
Work effort for each milestone (e.g. Milestone-1 = 3 points or small work effort, Milestone-2 = 5 or medium, Milestone-3 = 8 or large)
Work-effort weight for each Milestone (in %)
% or # of Completed tasks per a Milestone
How do I include the time in the equation? Say we have a start date and projected due date or duration (e.g. x weeks or days or months), I need to calculate the risk of completing a task (milestone and the entire MVP) on time based on the current # of tasks completed.
In other words, what is the risk (small/medium/large) that a Milestone/Milestones/MVP will be completed on time (say, Mar-31, 2023) based on the number of tasks completed (15 of 40)?
Please let me know if I need to clarify
I really appreciate any help you can provide.
The image is missing the time/deadline value so the risk is inaccurate current view
I am using the pyspark.ml.fpm (FP Growth) implementation of association rule mining on Spark v2.3.
The spark UI shows that the tasks as the end run very slowly. This seems to be a common problem and might be related to data skew.
Is this the real reason? Is there any solution for this?
I don't want to change the minSupport or minConfidence thresholds because that would effect by results. Removing the columns isn't a solution either.
I was facing a similar issue. One solution you might try is setting a threshold on the amount of products in a transaction. If there are a couple of transactions that have way more products than the average, the tree computed by FP Growth blows up. This causes the runtime increases significantly and the risk for memory errors is much higher.
Hence, doing outlier removal on the transactions with disproportional amount of products might do the trick.
Hope this helps you out a bit :)
Late answer but I also had an issue with long FPGrowth wait times, and the above answer really helped. Implemented as such to filter out anything that's above one standard deviation (this is after the transactions have been grouped):
def clean_transactions(df):
transactions_init = df.withColumn("basket_size", size("basket"))
print('---collecting stats')
df_stats = transactions_init.select(
_mean(col('basket_size')).alias('mean'),
_stddev(col('basket_size')).alias('std')
).collect()
mean = df_stats[0]['mean']
std = df_stats[0]['std']
max_ct = mean + std
print("--filtering out outliers")
transactions_cleaned = transactions_init.filter(transactions_init.basket_size <= max_ct)
return transactions_cleaned
I am testing anomaly detector on metrics of count of specific event per hour for last 90 days. For some reason I always get spikes (isPositive) only, but never drops, while I'm mostly interested to detect drops.
Data has weekly seasonality (expected drops on weekends) and definitely has abnormal drops mid week unusual for this day of week.
I also tried to play with specific hours to take them to extremely low for this time and week day. I tried different values for sensitivity (between 90 and 20).
On the positive side I get too many spikes, which create a lot of noise, while low sensitivity value didn't help to get rid of them.
Below is a link to request JSON.
Request JSON
You can try to set the maxRatio to 0.01, it should be what you expect.
Currently the sensitivity control is not good enough for low value. But we will rollout a new version in next week to improve it.
And you can also leverage https://aka.ms/addemo, and use a CSV to have more test.
If there are 10k busses and peak point is 9:30Am to 10:30Am, there will be 2% increase of Vusers every year then what is the throughput after 10 years?
Please help me how to solve this type of questions without using a tool.
Thanks in Advance.
The formula would be:
10000 * (1.02)^10 = 12190
With regards to implementation, 10000 busses (whatever it is) per our is 166 per minute or 2.7 per second which doesn't seem to be a very high load for me. Depending on your load testing tool there are different options on how to simulate it, for Apache JMeter it will be Constant Throughput Timer, for LoadRunner there are Pages per minute / Hits Per Second goals, etc.
So I am super stuck with this question and don't even know where to start from. This is the info I have:
Start to Finish Number of People per Day roundtrip
Seattle to Bainbridge 5,847 passengers 14.4 miles
Seattle to Tacoma, WA 3,243 passengers 40.2 miles
Bainbridge to Tacoma, WA 746 passengers 42 miles
This whole system costs 20 million. I need to develop different prices for the roundtrip tickets in a way that will be fair and understaandable to everyone. If the costs go from 20- 22 million, the system should be felxible to adjust for that too. The hint is to use equation "y=mx+b". This is the only information that I am given. Can anyone please help me where to even start? My idea was that we should charge Tacoma,WA passengers the most money cause it's less people and longest miles, second we should charge Seatle-Tacoma,WA passengers and finally the least amount should be charged to Seattle-Bainbridge passengers because it's the least miles and most passengers. Can you guys help me formulate this in an excel and how to get a head start with this one. |
I would really aprreciate the help,
Thanks,
Nika
Consider charging all passengers a specific amount per mile. The more you charge per mile, the more revenue you will generate on a daily basis.
At a minimum, the mileage rate should be set to generate enough money to cover the daily operating costs and create a maintenance reserve.
If you increase the mileage rate beyond this, you will also generate a cash stream that you can use to retire 20 million investment. The greater the rate the quicker the payback!